From ebdc6763613e89ff60008c414116d8badfddb86f Mon Sep 17 00:00:00 2001 From: fangfangssj <1135470306@qq.com> Date: Mon, 10 Nov 2025 20:11:58 +0800 Subject: [PATCH 1/4] add vaildator --- graph_net/test/decomposer_validator_test.sh | 36 ++++++ graph_net/test/naive_graph_decomposer_test.sh | 10 +- graph_net/torch/test_compiler.py | 2 + .../range_decomposer_validator.py | 117 +++++++++++++----- 4 files changed, 133 insertions(+), 32 deletions(-) create mode 100644 graph_net/test/decomposer_validator_test.sh diff --git a/graph_net/test/decomposer_validator_test.sh b/graph_net/test/decomposer_validator_test.sh new file mode 100644 index 000000000..d1cd12495 --- /dev/null +++ b/graph_net/test/decomposer_validator_test.sh @@ -0,0 +1,36 @@ +#!/bin/bash + +if [ -z "$GRAPH_NET_BENCHMARK_PATH" ]; then + GRAPH_NET_BENCHMARK_PATH="$(pwd)" +fi + +FILE_PATH=$GRAPH_NET_BENCHMARK_PATH/decomposer +mkdir -p "$(dirname "$FILE_PATH/log.log")" + +MODEL_PATH="./todo_works/range_decomposer_validator/test/simple_CNN" + +python -m graph_net.torch.test_compiler \ + --model-path $MODEL_PATH \ + --compiler range_decomposer_validator \ + --device cuda > "$FILE_PATH/log.log" 2>&1 + +if [ $? -ne 0 ]; then + echo "Error: decomposer_validator execution failed" + echo "Please check the log file: $FILE_PATH/log.log" + exit 1 +fi + +python -m graph_net.log2json \ + --log-file "$FILE_PATH/log.log" \ + --output-dir "$FILE_PATH/JSON_results/" + +python -m graph_net.plot_ESt \ + --benchmark-path "$FILE_PATH/JSON_results/" \ + --output-dir "$FILE_PATH" + +echo "==================================================" +echo "Results saved in: $FILE_PATH/ES_result.png" +echo "" +echo "IMPORTANT: Please verify if the curve in ES_result.png is a straight line" +echo "If the curve is NOT a straight line, please check the log file: $FILE_PATH/log.log" +echo "==================================================" \ No newline at end of file diff --git a/graph_net/test/naive_graph_decomposer_test.sh b/graph_net/test/naive_graph_decomposer_test.sh index 2d333266b..f3c4d7981 100644 --- a/graph_net/test/naive_graph_decomposer_test.sh +++ b/graph_net/test/naive_graph_decomposer_test.sh @@ -4,12 +4,15 @@ GRAPH_NET_ROOT=$(python3 -c "import graph_net; import os; print( os.path.dirname(graph_net.__file__))") # input model path -MODEL_PATH_IN_SAMPLES=/timm/resnet18 +MODEL_PATH_IN_SAMPLES=/timm/resnet18 +MODEL_NAME=$(basename "$MODEL_PATH_IN_SAMPLES") +OUTPUT_DIR="${NAIVE_DECOMPOSE_WORKSPACE:-$(pwd)/naive_decompose_workspace}" + extractor_config_json_str=$(cat < Any: + if isinstance(arg, torch.fx.Node): + return arg.name + if isinstance(arg, (list, tuple)): + return type(arg)(self._serialize_arg(elem) for elem in arg) + if isinstance(arg, dict): + return { + self._serialize_arg(k): self._serialize_arg(v) for k, v in arg.items() + } + return arg + + def _extract_operators_from_graph( + self, gm: nn.Module, example_inputs: List[torch.Tensor] = None + ) -> List[Dict[str, Any]]: + operator_list = [] + for node in gm.graph.nodes: + if node.op in ("call_method", "call_function", "call_module"): + operator_info = { + "op_type": node.op, + "target": node.target, + "name": node.name, + "kwargs": self._serialize_arg(node.kwargs), + } + + if isinstance(node.target, Callable): + try: + operator_info["target_name"] = node.target.__name__ + except AttributeError: + operator_info["target_name"] = str(node.target) + else: + operator_info["target_name"] = str(node.target) + + operator_list.append(operator_info) + + return operator_list + + def extract_compiler(self, gm: torch.fx.GraphModule, inputs: List[torch.Tensor]): + operator = self._extract_operators_from_graph(gm, inputs) + self.extract_node.append(operator) + return gm.forward def forward(self, **kwargs): current_args = kwargs + compiled_model = torch.compile(self.graph, backend=self.extract_compiler) + compiled_model(**current_args) + graph_node_list = list(itertools.chain.from_iterable(self.extract_node)) + self.extract_node = [] + for i, (sm, param_names) in enumerate( - zip(self.submodules, self.submodule_param_names) + zip(self.subgraph, self.subgraph_param_names) ): - # 准备当前子图的输入字典 call_kwargs = {} if i > 0: - # 对于后续子图，第一个参数是上一个子图的输出 first_param_name = param_names[0] - call_kwargs[first_param_name] = current_args # current_args 此时是上一个子图的输出 + call_kwargs[first_param_name] = current_args + remaining_params = param_names[1:] + else: + remaining_params = param_names - # 从主输入字典中筛选出当前子图需要的权重参数 - for name in param_names: - if name in current_args: - call_kwargs[name] = current_args[name] + for name in remaining_params: + if name in kwargs: + call_kwargs[name] = kwargs[name] - outputs = sm(**call_kwargs) - # 假设每个子图只有一个输出，并且返回的是一个元组 + compiled_model = torch.compile(sm, backend=self.extract_compiler) + outputs = compiled_model(**call_kwargs) current_args = outputs[0] + subgraph_node_list = list(itertools.chain.from_iterable(self.extract_node)) + self.extract_node = [] + + if graph_node_list != subgraph_node_list: + diff_in_graph = [ + item for item in graph_node_list if item not in subgraph_node_list + ] + diff_in_subgraph = [ + item for item in subgraph_node_list if item not in graph_node_list + ] + + error_msg = f"Subgraph segmentation verification failed\n" + error_msg += f"Nodes in graph but not in subgraph: {diff_in_graph}\n" + error_msg += f"Nodes in subgraph but not in graph: {diff_in_subgraph}" + raise ValueError(error_msg) + return (current_args,) @@ -54,36 +119,32 @@ def _load_model_instance(self, path: str, device: str) -> torch.nn.Module: return instance def __call__(self, model: torch.nn.Module) -> torch.nn.Module: - model_file_path = inspect.getfile( - model.__class__ - ) # e.g., /test/simple_CNN/model.py - model_dir = os.path.dirname(model_file_path) # e.g., /test/simple_CNN - - decomposed_parent_dir = ( - model_dir + "_decomposed" - ) # e.g., /test/simple_CNN_decomposed + model_file_path = model.__class__.__file_path__ + model_dir = os.path.dirname(model_file_path) + decomposed_parent_dir = model_dir + "_decomposed" subgraph_paths = [] for name in sorted(os.listdir(decomposed_parent_dir)): full_path = os.path.join(decomposed_parent_dir, name) - if os.path.isdir(full_path) and name.startswith("subgraph_"): + if os.path.isdir(full_path) and name[-1].isdigit(): subgraph_paths.append(full_path) print( f"[RangeDecomposerValidatorBackend] Found subgraphs: {[os.path.basename(p) for p in subgraph_paths]}" ) - submodule_instances = [] - device = next(model.parameters()).device # 从传入的model获取device信息 + device = model.__class__.__device__ + graph_instances = self._load_model_instance(model_dir, device) + subgraph_instances = [] for path in subgraph_paths: instance = self._load_model_instance(path, device) - submodule_instances.append(instance) + subgraph_instances.append(instance) dir_name = os.path.basename(path) print( f"[RangeDecomposerValidatorBackend] Loaded and instantiated '{dir_name}'" ) - composed_model = ComposedModel(submodule_instances) + composed_model = ComposedModel(graph_instances, subgraph_instances) return composed_model.eval() def synchronize(self): From 92a2d407bb050add86dbe906ba45a36836c72dc8 Mon Sep 17 00:00:00 2001 From: fangfangssj <1135470306@qq.com> Date: Tue, 11 Nov 2025 00:01:10 +0800 Subject: [PATCH 2/4] fix --- .../test/chain_naive_graph_decomposer_test.sh | 9 +- graph_net/test/decomposer_validator_test.sh | 4 +- graph_net/test/naive_graph_decomposer_test.sh | 10 +- .../range_decomposer_validator_backend.py | 46 +- graph_net/torch/test_compiler.py | 6 +- .../test/resnet18/graph_hash.txt | 1 + .../test/resnet18/graph_net.json | 7 + .../{simple_CNN => resnet18}/input_meta.py | 0 .../input_tensor_constraints.py | 0 .../test/resnet18/model.py | 977 +++++++++++++++ .../test/resnet18/weight_meta.py | 1064 +++++++++++++++++ .../resnet18_0/graph_net.json | 7 + .../resnet18_0}/input_meta.py | 0 .../resnet18_0}/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_0/model.py | 277 +++++ .../resnet18_0/weight_meta.py | 1028 ++++++++++++++++ .../resnet18_1/graph_net.json | 7 + .../resnet18_1}/input_meta.py | 0 .../resnet18_1}/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_1/model.py | 259 ++++ .../resnet18_1/weight_meta.py | 928 ++++++++++++++ .../resnet18_2/graph_net.json | 7 + .../resnet18_2}/input_meta.py | 0 .../resnet18_2}/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_2/model.py | 285 +++++ .../resnet18_2/weight_meta.py | 788 ++++++++++++ .../resnet18_3/graph_net.json | 7 + .../resnet18_3/input_meta.py} | 0 .../resnet18_3/input_tensor_constraints.py} | 0 .../resnet18_decomposed/resnet18_3/model.py | 365 ++++++ .../resnet18_3/weight_meta.py | 538 +++++++++ .../test/simple_CNN/graph_hash.txt | 1 - .../test/simple_CNN/model.py | 92 -- .../test/simple_CNN/weight_meta.py | 88 -- .../simple_CNN_decomposed/subgraph_0/model.py | 36 - .../subgraph_0/weight_meta.py | 28 - .../subgraph_1/graph_net.json | 0 .../simple_CNN_decomposed/subgraph_1/model.py | 35 - .../subgraph_1/weight_meta.py | 29 - .../subgraph_2/graph_net.json | 0 .../simple_CNN_decomposed/subgraph_2/model.py | 41 - .../subgraph_2/weight_meta.py | 49 - 42 files changed, 6579 insertions(+), 440 deletions(-) rename todo_works/range_decomposer_validator/range_decomposer_validator.py => graph_net/torch/backend/range_decomposer_validator_backend.py (79%) create mode 100644 todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt create mode 100644 todo_works/range_decomposer_validator/test/resnet18/graph_net.json rename todo_works/range_decomposer_validator/test/{simple_CNN => resnet18}/input_meta.py (100%) rename todo_works/range_decomposer_validator/test/{simple_CNN => resnet18}/input_tensor_constraints.py (100%) create mode 100644 todo_works/range_decomposer_validator/test/resnet18/model.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18/weight_meta.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_0 => resnet18_decomposed/resnet18_0}/input_meta.py (100%) rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_0 => resnet18_decomposed/resnet18_0}/input_tensor_constraints.py (100%) create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_1 => resnet18_decomposed/resnet18_1}/input_meta.py (100%) rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_1 => resnet18_decomposed/resnet18_1}/input_tensor_constraints.py (100%) create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_2 => resnet18_decomposed/resnet18_2}/input_meta.py (100%) rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_2 => resnet18_decomposed/resnet18_2}/input_tensor_constraints.py (100%) create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json rename todo_works/range_decomposer_validator/test/{simple_CNN/graph_net.json => resnet18_decomposed/resnet18_3/input_meta.py} (100%) rename todo_works/range_decomposer_validator/test/{simple_CNN_decomposed/subgraph_0/graph_net.json => resnet18_decomposed/resnet18_3/input_tensor_constraints.py} (100%) create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py create mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN/graph_hash.txt delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN/model.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/model.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/model.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/model.py delete mode 100644 todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/weight_meta.py diff --git a/graph_net/test/chain_naive_graph_decomposer_test.sh b/graph_net/test/chain_naive_graph_decomposer_test.sh index acdfd3f77..fe6755cba 100644 --- a/graph_net/test/chain_naive_graph_decomposer_test.sh +++ b/graph_net/test/chain_naive_graph_decomposer_test.sh @@ -4,12 +4,15 @@ GRAPH_NET_ROOT=$(python3 -c "import graph_net; import os; print( os.path.dirname(graph_net.__file__))") # input model path -MODEL_PATH_IN_SAMPLES=/timm/resnet18 +MODEL_PATH_IN_SAMPLES=/timm/resnet18 +MODEL_NAME=$(basename "$MODEL_PATH_IN_SAMPLES") +OUTPUT_DIR="${NAIVE_DECOMPOSE_WORKSPACE:-$(pwd)/naive_decompose_workspace}" + extractor_config_json_str=$(cat < Any: if isinstance(arg, torch.fx.Node): @@ -39,7 +36,6 @@ def _extract_operators_from_graph( operator_info = { "op_type": node.op, "target": node.target, - "name": node.name, "kwargs": self._serialize_arg(node.kwargs), } @@ -61,30 +57,26 @@ def extract_compiler(self, gm: torch.fx.GraphModule, inputs: List[torch.Tensor]) return gm.forward def forward(self, **kwargs): - current_args = kwargs - compiled_model = torch.compile(self.graph, backend=self.extract_compiler) - compiled_model(**current_args) + self.graph_model(**kwargs) graph_node_list = list(itertools.chain.from_iterable(self.extract_node)) self.extract_node = [] - for i, (sm, param_names) in enumerate( - zip(self.subgraph, self.subgraph_param_names) - ): - call_kwargs = {} - if i > 0: - first_param_name = param_names[0] - call_kwargs[first_param_name] = current_args - remaining_params = param_names[1:] - else: - remaining_params = param_names + subgraph_intput = { + key.replace("L", "l_l", 1): value + for key, value in kwargs.items() + if key.startswith("L") + } - for name in remaining_params: - if name in kwargs: - call_kwargs[name] = kwargs[name] + output = None + for subgraph_model in self.subgraph: + compiled_model = torch.compile( + subgraph_model, backend=self.extract_compiler + ) - compiled_model = torch.compile(sm, backend=self.extract_compiler) - outputs = compiled_model(**call_kwargs) - current_args = outputs[0] + if output is None: + output = compiled_model(**subgraph_intput) + else: + output = compiled_model(*output) subgraph_node_list = list(itertools.chain.from_iterable(self.extract_node)) self.extract_node = [] @@ -102,7 +94,7 @@ def forward(self, **kwargs): error_msg += f"Nodes in subgraph but not in graph: {diff_in_subgraph}" raise ValueError(error_msg) - return (current_args,) + return output class RangeDecomposerValidatorBackend: @@ -119,7 +111,7 @@ def _load_model_instance(self, path: str, device: str) -> torch.nn.Module: return instance def __call__(self, model: torch.nn.Module) -> torch.nn.Module: - model_file_path = model.__class__.__file_path__ + model_file_path = model.__class__.__graph_net_file_path__ model_dir = os.path.dirname(model_file_path) decomposed_parent_dir = model_dir + "_decomposed" subgraph_paths = [] @@ -132,7 +124,7 @@ def __call__(self, model: torch.nn.Module) -> torch.nn.Module: f"[RangeDecomposerValidatorBackend] Found subgraphs: {[os.path.basename(p) for p in subgraph_paths]}" ) - device = model.__class__.__device__ + device = model.__class__.__graph_net_device__ graph_instances = self._load_model_instance(model_dir, device) subgraph_instances = [] diff --git a/graph_net/torch/test_compiler.py b/graph_net/torch/test_compiler.py index 6d0f47c61..1095f24f5 100644 --- a/graph_net/torch/test_compiler.py +++ b/graph_net/torch/test_compiler.py @@ -23,7 +23,7 @@ from graph_net.torch.backend.blade_disc_backend import BladeDISCBackend from graph_net.torch.backend.nope_backend import NopeBackend from graph_net.torch.backend.unstable_to_stable_backend import UnstableToStableBackend -from todo_works.range_decomposer_validator.range_decomposer_validator import ( +from graph_net.torch.backend.range_decomposer_validator_backend import ( RangeDecomposerValidatorBackend, ) from graph_net.test_compiler_util import generate_allclose_configs @@ -69,8 +69,8 @@ def load_class_from_file( exec(compiled_code, module.__dict__) model_class = getattr(module, class_name, None) - setattr(model_class, "__file_path__", file_path) - setattr(model_class, "__device__", device) + setattr(model_class, "__graph_net_file_path__", file_path) + setattr(model_class, "__graph_net_device__", device) return model_class diff --git a/todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt b/todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt new file mode 100644 index 000000000..1e5df26ae --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt @@ -0,0 +1 @@ +248d46ebcf5bc02d3e72953ea430b5e18175b0419dbdbcd2479202497f58319d \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18/graph_net.json new file mode 100644 index 000000000..5a6dada2f --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18/graph_net.json @@ -0,0 +1,7 @@ +{ + "framework": "torch", + "num_devices_required": 1, + "num_nodes_required": 1, + "source": "timm", + "heuristic_tag": "computer_vision" +} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18/input_meta.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN/input_meta.py rename to todo_works/range_decomposer_validator/test/resnet18/input_meta.py diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18/input_tensor_constraints.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN/input_tensor_constraints.py rename to todo_works/range_decomposer_validator/test/resnet18/input_tensor_constraints.py diff --git a/todo_works/range_decomposer_validator/test/resnet18/model.py b/todo_works/range_decomposer_validator/test/resnet18/model.py new file mode 100644 index 000000000..0d741677b --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18/model.py @@ -0,0 +1,977 @@ +import torch + + +class GraphModule(torch.nn.Module): + def forward( + self, + L_self_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + s1: torch.SymInt, + L_x_: torch.Tensor, + L_self_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_: torch.Tensor, + L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_: torch.Tensor, + L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_: torch.Tensor, + L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, + L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, + L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, + L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, + L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, + L_self_modules_fc_parameters_weight_: torch.nn.parameter.Parameter, + L_self_modules_fc_parameters_bias_: torch.nn.parameter.Parameter, + ): + l_self_modules_conv1_parameters_weight_ = ( + L_self_modules_conv1_parameters_weight_ + ) + l_x_ = L_x_ + l_self_modules_bn1_buffers_running_mean_ = ( + L_self_modules_bn1_buffers_running_mean_ + ) + l_self_modules_bn1_buffers_running_var_ = ( + L_self_modules_bn1_buffers_running_var_ + ) + l_self_modules_bn1_parameters_weight_ = L_self_modules_bn1_parameters_weight_ + l_self_modules_bn1_parameters_bias_ = L_self_modules_bn1_parameters_bias_ + l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ = ( + L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ + ) + l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ = ( + L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ + ) + l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ = ( + L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ + ) + l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ = ( + L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ + ) + l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ = ( + L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ + ) + l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ = ( + L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ + ) + l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ = ( + L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ + ) + l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ = ( + L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ + ) + l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ = ( + L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ + ) + l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ = ( + L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ + ) + l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ = ( + L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ + ) + l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ = ( + L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ + ) + l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ = ( + L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ + ) + l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ = ( + L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ + ) + l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ = ( + L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ + ) + l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ = ( + L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ + ) + l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ = ( + L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ + ) + l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ = ( + L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ + ) + l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ = L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ + l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ + l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ + l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ + l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ + l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ = ( + L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ + ) + l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ = ( + L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ + ) + l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ = ( + L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ + ) + l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ = ( + L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ + ) + l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ = ( + L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ + ) + l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ = ( + L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ + ) + l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ = ( + L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ + ) + l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ = ( + L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ + ) + l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ = ( + L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ + ) + l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ = ( + L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ + ) + l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ = ( + L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ + ) + l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ = ( + L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ + ) + l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ = L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ + l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ + l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ + l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ + l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ + l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ = ( + L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ + ) + l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ = ( + L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ + ) + l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ = ( + L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ + ) + l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ = ( + L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ + ) + l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ = ( + L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ + ) + l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ = ( + L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ + ) + l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ = ( + L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ + ) + l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ = ( + L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ + ) + l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ = ( + L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ + ) + l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ = ( + L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ + ) + l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ = ( + L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ + ) + l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ = ( + L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ + ) + l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ = L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ + l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ + l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ + l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ + l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ + l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ = ( + L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ + ) + l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ = ( + L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ + ) + l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ = ( + L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ + ) + l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ = ( + L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ + ) + l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ = ( + L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ + ) + l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ = ( + L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ + ) + l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ = ( + L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ + ) + l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ = ( + L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ + ) + l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ = ( + L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ + ) + l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ = ( + L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ + ) + l_self_modules_fc_parameters_weight_ = L_self_modules_fc_parameters_weight_ + l_self_modules_fc_parameters_bias_ = L_self_modules_fc_parameters_bias_ + x = torch.conv2d( + l_x_, + l_self_modules_conv1_parameters_weight_, + None, + (2, 2), + (3, 3), + (1, 1), + 1, + ) + l_x_ = l_self_modules_conv1_parameters_weight_ = None + x_1 = torch.nn.functional.batch_norm( + x, + l_self_modules_bn1_buffers_running_mean_, + l_self_modules_bn1_buffers_running_var_, + l_self_modules_bn1_parameters_weight_, + l_self_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x = ( + l_self_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_bn1_parameters_weight_ + ) = l_self_modules_bn1_parameters_bias_ = None + x_2 = torch.nn.functional.relu(x_1, inplace=True) + x_1 = None + x_3 = torch.nn.functional.max_pool2d( + x_2, 3, 2, 1, 1, ceil_mode=False, return_indices=False + ) + x_2 = None + x_4 = torch.conv2d( + x_3, + l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ = None + x_5 = torch.nn.functional.batch_norm( + x_4, + l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_, + l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_, + l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_, + l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_4 = ( + l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ + ) = l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ = None + x_6 = torch.nn.functional.relu(x_5, inplace=True) + x_5 = None + x_7 = torch.conv2d( + x_6, + l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_6 = l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ = None + x_8 = torch.nn.functional.batch_norm( + x_7, + l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, + l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, + l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, + l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_7 = ( + l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ + ) = l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ = None + x_8 += x_3 + x_9 = x_8 + x_8 = x_3 = None + x_10 = torch.nn.functional.relu(x_9, inplace=True) + x_9 = None + x_11 = torch.conv2d( + x_10, + l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ = None + x_12 = torch.nn.functional.batch_norm( + x_11, + l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, + l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, + l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, + l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_11 = ( + l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ + ) = l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ = None + x_13 = torch.nn.functional.relu(x_12, inplace=True) + x_12 = None + x_14 = torch.conv2d( + x_13, + l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_13 = l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ = None + x_15 = torch.nn.functional.batch_norm( + x_14, + l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, + l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, + l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, + l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_14 = ( + l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ + ) = l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ = None + x_15 += x_10 + x_16 = x_15 + x_15 = x_10 = None + x_17 = torch.nn.functional.relu(x_16, inplace=True) + x_16 = None + x_18 = torch.conv2d( + x_17, + l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + None, + (2, 2), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ = None + x_19 = torch.nn.functional.batch_norm( + x_18, + l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_18 = ( + l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ + ) = l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ = None + x_20 = torch.nn.functional.relu(x_19, inplace=True) + x_19 = None + x_21 = torch.conv2d( + x_20, + l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_20 = l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ = None + x_22 = torch.nn.functional.batch_norm( + x_21, + l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_21 = ( + l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ + ) = l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ = None + input_1 = torch.conv2d( + x_17, + l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + None, + (2, 2), + (0, 0), + (1, 1), + 1, + ) + x_17 = l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) + input_2 = torch.nn.functional.batch_norm( + input_1, + l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + input_1 = l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ = l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) + x_22 += input_2 + x_23 = x_22 + x_22 = input_2 = None + x_24 = torch.nn.functional.relu(x_23, inplace=True) + x_23 = None + x_25 = torch.conv2d( + x_24, + l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ = None + x_26 = torch.nn.functional.batch_norm( + x_25, + l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_25 = ( + l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ + ) = l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ = None + x_27 = torch.nn.functional.relu(x_26, inplace=True) + x_26 = None + x_28 = torch.conv2d( + x_27, + l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_27 = l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ = None + x_29 = torch.nn.functional.batch_norm( + x_28, + l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_28 = ( + l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ + ) = l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ = None + x_29 += x_24 + x_30 = x_29 + x_29 = x_24 = None + x_31 = torch.nn.functional.relu(x_30, inplace=True) + x_30 = None + x_32 = torch.conv2d( + x_31, + l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + None, + (2, 2), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ = None + x_33 = torch.nn.functional.batch_norm( + x_32, + l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_32 = ( + l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ + ) = l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ = None + x_34 = torch.nn.functional.relu(x_33, inplace=True) + x_33 = None + x_35 = torch.conv2d( + x_34, + l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_34 = l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ = None + x_36 = torch.nn.functional.batch_norm( + x_35, + l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_35 = ( + l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ + ) = l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ = None + input_3 = torch.conv2d( + x_31, + l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + None, + (2, 2), + (0, 0), + (1, 1), + 1, + ) + x_31 = l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) + input_4 = torch.nn.functional.batch_norm( + input_3, + l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + input_3 = l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ = l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) + x_36 += input_4 + x_37 = x_36 + x_36 = input_4 = None + x_38 = torch.nn.functional.relu(x_37, inplace=True) + x_37 = None + x_39 = torch.conv2d( + x_38, + l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ = None + x_40 = torch.nn.functional.batch_norm( + x_39, + l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_39 = ( + l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ + ) = l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ = None + x_41 = torch.nn.functional.relu(x_40, inplace=True) + x_40 = None + x_42 = torch.conv2d( + x_41, + l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_41 = l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ = None + x_43 = torch.nn.functional.batch_norm( + x_42, + l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_42 = ( + l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ + ) = l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ = None + x_43 += x_38 + x_44 = x_43 + x_43 = x_38 = None + x_45 = torch.nn.functional.relu(x_44, inplace=True) + x_44 = None + x_46 = torch.conv2d( + x_45, + l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + None, + (2, 2), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ = None + x_47 = torch.nn.functional.batch_norm( + x_46, + l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_46 = ( + l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ + ) = l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ = None + x_48 = torch.nn.functional.relu(x_47, inplace=True) + x_47 = None + x_49 = torch.conv2d( + x_48, + l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_48 = l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ = None + x_50 = torch.nn.functional.batch_norm( + x_49, + l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_49 = ( + l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ + ) = l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ = None + input_5 = torch.conv2d( + x_45, + l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + None, + (2, 2), + (0, 0), + (1, 1), + 1, + ) + x_45 = l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) + input_6 = torch.nn.functional.batch_norm( + input_5, + l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + input_5 = l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ = l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) + x_50 += input_6 + x_51 = x_50 + x_50 = input_6 = None + x_52 = torch.nn.functional.relu(x_51, inplace=True) + x_51 = None + x_53 = torch.conv2d( + x_52, + l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ = None + x_54 = torch.nn.functional.batch_norm( + x_53, + l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_53 = ( + l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ + ) = l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ = None + x_55 = torch.nn.functional.relu(x_54, inplace=True) + x_54 = None + x_56 = torch.conv2d( + x_55, + l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_55 = l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ = None + x_57 = torch.nn.functional.batch_norm( + x_56, + l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_56 = ( + l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ + ) = l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ = None + x_57 += x_52 + x_58 = x_57 + x_57 = x_52 = None + x_59 = torch.nn.functional.relu(x_58, inplace=True) + x_58 = None + x_60 = torch.nn.functional.adaptive_avg_pool2d(x_59, 1) + x_59 = None + x_61 = x_60.flatten(1, -1) + x_60 = None + x_62 = torch._C._nn.linear( + x_61, + l_self_modules_fc_parameters_weight_, + l_self_modules_fc_parameters_bias_, + ) + x_61 = ( + l_self_modules_fc_parameters_weight_ + ) = l_self_modules_fc_parameters_bias_ = None + return (x_62,) diff --git a/todo_works/range_decomposer_validator/test/resnet18/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18/weight_meta.py new file mode 100644 index 000000000..4f1762837 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18/weight_meta.py @@ -0,0 +1,1064 @@ +class Program_weight_tensor_meta_L_self_modules_conv1_parameters_weight_: + name = "L_self_modules_conv1_parameters_weight_" + shape = [64, 3, 7, 7] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.235 + data = None + + +class Program_weight_tensor_meta_s1: + name = "s1" + shape = [] + dtype = "torch.int64" + device = "cpu" + mean = None + std = None + data = [4] + + +class Program_weight_tensor_meta_L_x_: + name = "L_x_" + shape = [1, 3, 224, 224] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.225 + std = 1.283 + data = None + + +class Program_weight_tensor_meta_L_self_modules_bn1_buffers_running_mean_: + name = "L_self_modules_bn1_buffers_running_mean_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.003 + std = 0.123 + data = None + + +class Program_weight_tensor_meta_L_self_modules_bn1_buffers_running_var_: + name = "L_self_modules_bn1_buffers_running_var_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 30.655 + std = 90.134 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_bn1_parameters_weight_: + name = "L_self_modules_bn1_parameters_weight_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.285 + std = 0.584 + data = None + + +class Program_weight_tensor_meta_L_self_modules_bn1_parameters_bias_: + name = "L_self_modules_bn1_parameters_bias_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.003 + std = 1.814 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_: + name = "L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.261 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -12.479 + std = 21.250 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 255.163 + std = 382.886 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_: + name = "L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.781 + std = 0.500 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_: + name = "L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.329 + std = 0.957 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_: + name = "L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.247 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.144 + std = 3.496 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 7.302 + std = 6.209 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_: + name = "L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.275 + std = 1.835 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_: + name = "L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.776 + std = 1.979 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_: + name = "L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.014 + std = 0.268 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -7.661 + std = 17.322 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 170.317 + std = 247.345 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_: + name = "L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.234 + std = 0.433 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_: + name = "L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.462 + std = 0.714 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_: + name = "L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.003 + std = 0.260 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.021 + std = 2.934 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 11.941 + std = 4.796 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_: + name = "L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.135 + std = 2.538 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_: + name = "L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.356 + std = 1.532 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_: + name = "L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_" + shape = [128, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.260 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -4.639 + std = 12.326 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 330.088 + std = 148.934 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_: + name = "L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.498 + std = 0.448 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_: + name = "L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.591 + std = 1.256 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_: + name = "L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.250 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.625 + std = 8.374 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 58.237 + std = 28.224 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_: + name = "L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.147 + std = 1.901 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_: + name = "L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.750 + std = 1.177 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_: + name = "L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_" + shape = [128, 64, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.271 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_: + name = "L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.265 + std = 5.294 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_: + name = "L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 17.639 + std = 6.164 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_: + name = "L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.093 + std = 0.581 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_: + name = ( + "L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_" + ) + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.527 + std = 1.374 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_: + name = "L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.255 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -13.675 + std = 12.174 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 229.209 + std = 140.985 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_: + name = "L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.604 + std = 0.540 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_: + name = "L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.286 + std = 1.304 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_: + name = "L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.249 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.113 + std = 3.676 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 35.213 + std = 19.076 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_: + name = "L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.085 + std = 2.327 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_: + name = "L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.986 + std = 2.047 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_: + name = "L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_" + shape = [256, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.243 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -11.722 + std = 12.927 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 503.389 + std = 202.299 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_: + name = "L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.966 + std = 0.549 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_: + name = "L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.318 + std = 1.221 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_: + name = "L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.234 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.036 + std = 12.437 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 143.320 + std = 56.891 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_: + name = "L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.182 + std = 2.144 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_: + name = "L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.152 + std = 1.357 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_: + name = "L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_" + shape = [256, 128, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.008 + std = 0.252 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_: + name = "L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.227 + std = 3.560 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_: + name = "L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 33.534 + std = 16.507 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_: + name = "L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.076 + std = 0.477 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_: + name = ( + "L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_" + ) + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.147 + std = 1.038 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_: + name = "L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.018 + std = 0.233 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -19.051 + std = 14.547 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 367.899 + std = 226.211 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_: + name = "L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.596 + std = 0.600 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_: + name = "L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.734 + std = 1.526 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_: + name = "L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.229 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.113 + std = 5.289 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 36.753 + std = 9.020 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_: + name = "L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.047 + std = 2.414 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_: + name = "L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.184 + std = 1.609 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_: + name = "L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_" + shape = [512, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.023 + std = 0.218 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -40.197 + std = 18.273 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 877.771 + std = 369.567 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_: + name = "L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.590 + std = 0.479 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_: + name = "L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.139 + std = 1.248 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_: + name = "L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.205 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.093 + std = 5.875 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 31.290 + std = 13.348 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_: + name = "L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.036 + std = 1.672 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_: + name = "L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.322 + std = 0.698 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_: + name = "L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_" + shape = [512, 256, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.239 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_: + name = "L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.977 + std = 3.562 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_: + name = "L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 40.350 + std = 12.568 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_: + name = "L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.331 + std = 0.395 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_: + name = ( + "L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_" + ) + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.963 + std = 0.855 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_: + name = "L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.025 + std = 0.201 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_: + name = "L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -19.941 + std = 7.969 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_: + name = "L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 271.009 + std = 148.261 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_: + name = "L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.420 + std = 0.661 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_: + name = "L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.482 + std = 1.753 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_: + name = "L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.193 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_: + name = "L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.020 + std = 3.287 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_: + name = "L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 10.217 + std = 3.587 + data = None + min_val = 0 + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_: + name = "L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.013 + std = 1.906 + data = None + + +class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_: + name = "L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.886 + std = 0.808 + data = None + + +class Program_weight_tensor_meta_L_self_modules_fc_parameters_weight_: + name = "L_self_modules_fc_parameters_weight_" + shape = [1000, 512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.046 + std = 0.273 + data = None + + +class Program_weight_tensor_meta_L_self_modules_fc_parameters_bias_: + name = "L_self_modules_fc_parameters_bias_" + shape = [1000] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.514 + std = 0.327 + data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json new file mode 100644 index 000000000..1300cd837 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json @@ -0,0 +1,7 @@ +{ + "framework": "torch", + "num_devices_required": 1, + "num_nodes_required": 1, + "dynamic": false, + "model_name": "resnet18_0" +} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_meta.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/input_meta.py rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_meta.py diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_tensor_constraints.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/input_tensor_constraints.py rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_tensor_constraints.py diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py new file mode 100644 index 000000000..48c10d00a --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py @@ -0,0 +1,277 @@ +import torch + + +class GraphModule(torch.nn.Module): + def forward( + self, + l_l_self_modules_bn1_buffers_running_mean_, + l_l_self_modules_bn1_buffers_running_var_, + l_l_self_modules_bn1_parameters_bias_, + l_l_self_modules_bn1_parameters_weight_, + l_l_self_modules_conv1_parameters_weight_, + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + l_l_x_, + ): + x = torch.conv2d( + l_l_x_, + l_l_self_modules_conv1_parameters_weight_, + None, + (2, 2), + (3, 3), + (1, 1), + 1, + ) + l_l_x_ = l_l_self_modules_conv1_parameters_weight_ = None + x_1 = torch.nn.functional.batch_norm( + x, + l_l_self_modules_bn1_buffers_running_mean_, + l_l_self_modules_bn1_buffers_running_var_, + l_l_self_modules_bn1_parameters_weight_, + l_l_self_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x = ( + l_l_self_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_bn1_parameters_weight_ + ) = l_l_self_modules_bn1_parameters_bias_ = None + x_2 = torch.nn.functional.relu(x_1, inplace=True) + x_1 = None + x_3 = torch.nn.functional.max_pool2d( + x_2, 3, 2, 1, 1, ceil_mode=False, return_indices=False + ) + x_2 = None + x_4 = torch.conv2d( + x_3, + l_l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ = None + x_5 = torch.nn.functional.batch_norm( + x_4, + l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_4 = ( + l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ = None + x_6 = torch.nn.functional.relu(x_5, inplace=True) + x_5 = None + x_7 = torch.conv2d( + x_6, + l_l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_6 = l_l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ = None + return ( + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + x_3, + x_7, + ) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py new file mode 100644 index 000000000..caa3b2f20 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py @@ -0,0 +1,1028 @@ +class Program_weight_tensor_meta_v0: + name = "v0" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.002 + std = 0.024 + data = None + + +class Program_weight_tensor_meta_v2: + name = "v2" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 32.728 + std = 16.008 + data = None + + +class Program_weight_tensor_meta_v4: + name = "v4" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.914 + std = 0.338 + data = None + + +class Program_weight_tensor_meta_v6: + name = "v6" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.287 + std = 0.119 + data = None + + +class Program_weight_tensor_meta_v8: + name = "v8" + shape = [64, 3, 7, 7] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v10: + name = "v10" + shape = [1000] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.514 + std = 0.066 + data = None + + +class Program_weight_tensor_meta_v12: + name = "v12" + shape = [1000, 512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.046 + std = 0.055 + data = None + + +class Program_weight_tensor_meta_v14: + name = "v14" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -11.456 + std = 3.783 + data = None + + +class Program_weight_tensor_meta_v16: + name = "v16" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 99.144 + std = 4.455 + data = None + + +class Program_weight_tensor_meta_v18: + name = "v18" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.385 + std = 0.208 + data = None + + +class Program_weight_tensor_meta_v20: + name = "v20" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.788 + std = 0.105 + data = None + + +class Program_weight_tensor_meta_v22: + name = "v22" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.134 + std = 0.580 + data = None + + +class Program_weight_tensor_meta_v24: + name = "v24" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 7.212 + std = 1.287 + data = None + + +class Program_weight_tensor_meta_v26: + name = "v26" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.756 + std = 0.372 + data = None + + +class Program_weight_tensor_meta_v28: + name = "v28" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.258 + std = 0.399 + data = None + + +class Program_weight_tensor_meta_v30: + name = "v30" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.052 + data = None + + +class Program_weight_tensor_meta_v32: + name = "v32" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.049 + data = None + + +class Program_weight_tensor_meta_v34: + name = "v34" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -8.395 + std = 3.176 + data = None + + +class Program_weight_tensor_meta_v36: + name = "v36" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 96.830 + std = 12.050 + data = None + + +class Program_weight_tensor_meta_v38: + name = "v38" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.463 + std = 0.130 + data = None + + +class Program_weight_tensor_meta_v40: + name = "v40" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.228 + std = 0.094 + data = None + + +class Program_weight_tensor_meta_v42: + name = "v42" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.023 + std = 0.519 + data = None + + +class Program_weight_tensor_meta_v44: + name = "v44" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 11.859 + std = 1.057 + data = None + + +class Program_weight_tensor_meta_v46: + name = "v46" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.376 + std = 0.298 + data = None + + +class Program_weight_tensor_meta_v48: + name = "v48" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.127 + std = 0.538 + data = None + + +class Program_weight_tensor_meta_v50: + name = "v50" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.014 + std = 0.054 + data = None + + +class Program_weight_tensor_meta_v52: + name = "v52" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.003 + std = 0.052 + data = None + + +class Program_weight_tensor_meta_v54: + name = "v54" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -4.751 + std = 2.747 + data = None + + +class Program_weight_tensor_meta_v56: + name = "v56" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v58: + name = "v58" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.565 + std = 0.247 + data = None + + +class Program_weight_tensor_meta_v60: + name = "v60" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.496 + std = 0.084 + data = None + + +class Program_weight_tensor_meta_v62: + name = "v62" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.645 + std = 1.716 + data = None + + +class Program_weight_tensor_meta_v64: + name = "v64" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 58.118 + std = 5.192 + data = None + + +class Program_weight_tensor_meta_v66: + name = "v66" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.747 + std = 0.232 + data = None + + +class Program_weight_tensor_meta_v68: + name = "v68" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.160 + std = 0.355 + data = None + + +class Program_weight_tensor_meta_v70: + name = "v70" + shape = [128, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.052 + data = None + + +class Program_weight_tensor_meta_v72: + name = "v72" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v74: + name = "v74" + shape = [128, 64, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.054 + data = None + + +class Program_weight_tensor_meta_v76: + name = "v76" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.302 + std = 1.015 + data = None + + +class Program_weight_tensor_meta_v78: + name = "v78" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 17.628 + std = 1.354 + data = None + + +class Program_weight_tensor_meta_v80: + name = "v80" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.518 + std = 0.234 + data = None + + +class Program_weight_tensor_meta_v82: + name = "v82" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.106 + std = 0.106 + data = None + + +class Program_weight_tensor_meta_v84: + name = "v84" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -13.357 + std = 2.853 + data = None + + +class Program_weight_tensor_meta_v86: + name = "v86" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v88: + name = "v88" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.293 + std = 0.257 + data = None + + +class Program_weight_tensor_meta_v90: + name = "v90" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.617 + std = 0.102 + data = None + + +class Program_weight_tensor_meta_v92: + name = "v92" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.066 + std = 0.746 + data = None + + +class Program_weight_tensor_meta_v94: + name = "v94" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 34.897 + std = 4.158 + data = None + + +class Program_weight_tensor_meta_v96: + name = "v96" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.954 + std = 0.453 + data = None + + +class Program_weight_tensor_meta_v98: + name = "v98" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.058 + std = 0.477 + data = None + + +class Program_weight_tensor_meta_v100: + name = "v100" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.051 + data = None + + +class Program_weight_tensor_meta_v102: + name = "v102" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v104: + name = "v104" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -11.724 + std = 2.568 + data = None + + +class Program_weight_tensor_meta_v106: + name = "v106" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v108: + name = "v108" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.309 + std = 0.249 + data = None + + +class Program_weight_tensor_meta_v110: + name = "v110" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.956 + std = 0.105 + data = None + + +class Program_weight_tensor_meta_v112: + name = "v112" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.036 + std = 2.517 + data = None + + +class Program_weight_tensor_meta_v114: + name = "v114" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v116: + name = "v116" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.161 + std = 0.255 + data = None + + +class Program_weight_tensor_meta_v118: + name = "v118" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.180 + std = 0.421 + data = None + + +class Program_weight_tensor_meta_v120: + name = "v120" + shape = [256, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.049 + data = None + + +class Program_weight_tensor_meta_v122: + name = "v122" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v124: + name = "v124" + shape = [256, 128, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.008 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v126: + name = "v126" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.276 + std = 0.731 + data = None + + +class Program_weight_tensor_meta_v128: + name = "v128" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 33.667 + std = 3.078 + data = None + + +class Program_weight_tensor_meta_v130: + name = "v130" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.133 + std = 0.196 + data = None + + +class Program_weight_tensor_meta_v132: + name = "v132" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.080 + std = 0.093 + data = None + + +class Program_weight_tensor_meta_v134: + name = "v134" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -18.895 + std = 2.806 + data = None + + +class Program_weight_tensor_meta_v136: + name = "v136" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v138: + name = "v138" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.732 + std = 0.294 + data = None + + +class Program_weight_tensor_meta_v140: + name = "v140" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.591 + std = 0.122 + data = None + + +class Program_weight_tensor_meta_v142: + name = "v142" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.197 + std = 1.055 + data = None + + +class Program_weight_tensor_meta_v144: + name = "v144" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 36.599 + std = 1.702 + data = None + + +class Program_weight_tensor_meta_v146: + name = "v146" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.189 + std = 0.297 + data = None + + +class Program_weight_tensor_meta_v148: + name = "v148" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.012 + std = 0.482 + data = None + + +class Program_weight_tensor_meta_v150: + name = "v150" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.018 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v152: + name = "v152" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.046 + data = None + + +class Program_weight_tensor_meta_v154: + name = "v154" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -40.390 + std = 3.518 + data = None + + +class Program_weight_tensor_meta_v156: + name = "v156" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v158: + name = "v158" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.130 + std = 0.250 + data = None + + +class Program_weight_tensor_meta_v160: + name = "v160" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.580 + std = 0.097 + data = None + + +class Program_weight_tensor_meta_v162: + name = "v162" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.200 + std = 1.217 + data = None + + +class Program_weight_tensor_meta_v164: + name = "v164" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 31.269 + std = 2.720 + data = None + + +class Program_weight_tensor_meta_v166: + name = "v166" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.319 + std = 0.136 + data = None + + +class Program_weight_tensor_meta_v168: + name = "v168" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.076 + std = 0.344 + data = None + + +class Program_weight_tensor_meta_v170: + name = "v170" + shape = [512, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.023 + std = 0.044 + data = None + + +class Program_weight_tensor_meta_v172: + name = "v172" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.041 + data = None + + +class Program_weight_tensor_meta_v174: + name = "v174" + shape = [512, 256, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.048 + data = None + + +class Program_weight_tensor_meta_v176: + name = "v176" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.973 + std = 0.717 + data = None + + +class Program_weight_tensor_meta_v178: + name = "v178" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 40.412 + std = 2.406 + data = None + + +class Program_weight_tensor_meta_v180: + name = "v180" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.976 + std = 0.169 + data = None + + +class Program_weight_tensor_meta_v182: + name = "v182" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.327 + std = 0.080 + data = None + + +class Program_weight_tensor_meta_v184: + name = "v184" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -19.917 + std = 1.532 + data = None + + +class Program_weight_tensor_meta_v186: + name = "v186" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v188: + name = "v188" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.472 + std = 0.364 + data = None + + +class Program_weight_tensor_meta_v190: + name = "v190" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.425 + std = 0.131 + data = None + + +class Program_weight_tensor_meta_v192: + name = "v192" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.046 + std = 0.648 + data = None + + +class Program_weight_tensor_meta_v194: + name = "v194" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 10.253 + std = 0.739 + data = None + + +class Program_weight_tensor_meta_v196: + name = "v196" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.889 + std = 0.160 + data = None + + +class Program_weight_tensor_meta_v198: + name = "v198" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.020 + std = 0.392 + data = None + + +class Program_weight_tensor_meta_v200: + name = "v200" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.025 + std = 0.040 + data = None + + +class Program_weight_tensor_meta_v202: + name = "v202" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.039 + data = None + + +class Program_weight_tensor_meta_v204: + name = "v204" + shape = [1, 3, 224, 224] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.224 + std = 0.255 + data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json new file mode 100644 index 000000000..380168032 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json @@ -0,0 +1,7 @@ +{ + "framework": "torch", + "num_devices_required": 1, + "num_nodes_required": 1, + "dynamic": false, + "model_name": "resnet18_1" +} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_meta.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/input_meta.py rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_meta.py diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_tensor_constraints.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/input_tensor_constraints.py rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_tensor_constraints.py diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py new file mode 100644 index 000000000..d545f143d --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py @@ -0,0 +1,259 @@ +import torch + + +class GraphModule(torch.nn.Module): + def forward( + self, + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + x_3, + x_7, + ): + x_8 = torch.nn.functional.batch_norm( + x_7, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_7 = ( + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ = None + x_8 += x_3 + x_9 = x_8 + x_8 = x_3 = None + x_10 = torch.nn.functional.relu(x_9, inplace=True) + x_9 = None + x_11 = torch.conv2d( + x_10, + l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ = None + x_12 = torch.nn.functional.batch_norm( + x_11, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_11 = ( + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ = None + x_13 = torch.nn.functional.relu(x_12, inplace=True) + x_12 = None + x_14 = torch.conv2d( + x_13, + l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_13 = l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ = None + x_15 = torch.nn.functional.batch_norm( + x_14, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_14 = ( + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ = None + return ( + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + x_10, + x_15, + ) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py new file mode 100644 index 000000000..b1a3a373e --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py @@ -0,0 +1,928 @@ +class Program_weight_tensor_meta_v0: + name = "v0" + shape = [1000] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.514 + std = 0.066 + data = None + + +class Program_weight_tensor_meta_v2: + name = "v2" + shape = [1000, 512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.046 + std = 0.055 + data = None + + +class Program_weight_tensor_meta_v4: + name = "v4" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.134 + std = 0.580 + data = None + + +class Program_weight_tensor_meta_v6: + name = "v6" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 7.212 + std = 1.287 + data = None + + +class Program_weight_tensor_meta_v8: + name = "v8" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.756 + std = 0.372 + data = None + + +class Program_weight_tensor_meta_v10: + name = "v10" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.258 + std = 0.399 + data = None + + +class Program_weight_tensor_meta_v12: + name = "v12" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -8.395 + std = 3.176 + data = None + + +class Program_weight_tensor_meta_v14: + name = "v14" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 96.830 + std = 12.050 + data = None + + +class Program_weight_tensor_meta_v16: + name = "v16" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.463 + std = 0.130 + data = None + + +class Program_weight_tensor_meta_v18: + name = "v18" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.228 + std = 0.094 + data = None + + +class Program_weight_tensor_meta_v20: + name = "v20" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.023 + std = 0.519 + data = None + + +class Program_weight_tensor_meta_v22: + name = "v22" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = 11.859 + std = 1.057 + data = None + + +class Program_weight_tensor_meta_v24: + name = "v24" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.376 + std = 0.298 + data = None + + +class Program_weight_tensor_meta_v26: + name = "v26" + shape = [64] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.127 + std = 0.538 + data = None + + +class Program_weight_tensor_meta_v28: + name = "v28" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.014 + std = 0.054 + data = None + + +class Program_weight_tensor_meta_v30: + name = "v30" + shape = [64, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.003 + std = 0.052 + data = None + + +class Program_weight_tensor_meta_v32: + name = "v32" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -4.751 + std = 2.747 + data = None + + +class Program_weight_tensor_meta_v34: + name = "v34" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v36: + name = "v36" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.565 + std = 0.247 + data = None + + +class Program_weight_tensor_meta_v38: + name = "v38" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.496 + std = 0.084 + data = None + + +class Program_weight_tensor_meta_v40: + name = "v40" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.645 + std = 1.716 + data = None + + +class Program_weight_tensor_meta_v42: + name = "v42" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 58.118 + std = 5.192 + data = None + + +class Program_weight_tensor_meta_v44: + name = "v44" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.747 + std = 0.232 + data = None + + +class Program_weight_tensor_meta_v46: + name = "v46" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.160 + std = 0.355 + data = None + + +class Program_weight_tensor_meta_v48: + name = "v48" + shape = [128, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.052 + data = None + + +class Program_weight_tensor_meta_v50: + name = "v50" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v52: + name = "v52" + shape = [128, 64, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.054 + data = None + + +class Program_weight_tensor_meta_v54: + name = "v54" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.302 + std = 1.015 + data = None + + +class Program_weight_tensor_meta_v56: + name = "v56" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 17.628 + std = 1.354 + data = None + + +class Program_weight_tensor_meta_v58: + name = "v58" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.518 + std = 0.234 + data = None + + +class Program_weight_tensor_meta_v60: + name = "v60" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.106 + std = 0.106 + data = None + + +class Program_weight_tensor_meta_v62: + name = "v62" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -13.357 + std = 2.853 + data = None + + +class Program_weight_tensor_meta_v64: + name = "v64" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v66: + name = "v66" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.293 + std = 0.257 + data = None + + +class Program_weight_tensor_meta_v68: + name = "v68" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.617 + std = 0.102 + data = None + + +class Program_weight_tensor_meta_v70: + name = "v70" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.066 + std = 0.746 + data = None + + +class Program_weight_tensor_meta_v72: + name = "v72" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 34.897 + std = 4.158 + data = None + + +class Program_weight_tensor_meta_v74: + name = "v74" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.954 + std = 0.453 + data = None + + +class Program_weight_tensor_meta_v76: + name = "v76" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.058 + std = 0.477 + data = None + + +class Program_weight_tensor_meta_v78: + name = "v78" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.051 + data = None + + +class Program_weight_tensor_meta_v80: + name = "v80" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v82: + name = "v82" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -11.724 + std = 2.568 + data = None + + +class Program_weight_tensor_meta_v84: + name = "v84" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v86: + name = "v86" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.309 + std = 0.249 + data = None + + +class Program_weight_tensor_meta_v88: + name = "v88" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.956 + std = 0.105 + data = None + + +class Program_weight_tensor_meta_v90: + name = "v90" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.036 + std = 2.517 + data = None + + +class Program_weight_tensor_meta_v92: + name = "v92" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v94: + name = "v94" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.161 + std = 0.255 + data = None + + +class Program_weight_tensor_meta_v96: + name = "v96" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.180 + std = 0.421 + data = None + + +class Program_weight_tensor_meta_v98: + name = "v98" + shape = [256, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.049 + data = None + + +class Program_weight_tensor_meta_v100: + name = "v100" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v102: + name = "v102" + shape = [256, 128, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.008 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v104: + name = "v104" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.276 + std = 0.731 + data = None + + +class Program_weight_tensor_meta_v106: + name = "v106" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 33.667 + std = 3.078 + data = None + + +class Program_weight_tensor_meta_v108: + name = "v108" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.133 + std = 0.196 + data = None + + +class Program_weight_tensor_meta_v110: + name = "v110" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.080 + std = 0.093 + data = None + + +class Program_weight_tensor_meta_v112: + name = "v112" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -18.895 + std = 2.806 + data = None + + +class Program_weight_tensor_meta_v114: + name = "v114" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v116: + name = "v116" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.732 + std = 0.294 + data = None + + +class Program_weight_tensor_meta_v118: + name = "v118" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.591 + std = 0.122 + data = None + + +class Program_weight_tensor_meta_v120: + name = "v120" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.197 + std = 1.055 + data = None + + +class Program_weight_tensor_meta_v122: + name = "v122" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 36.599 + std = 1.702 + data = None + + +class Program_weight_tensor_meta_v124: + name = "v124" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.189 + std = 0.297 + data = None + + +class Program_weight_tensor_meta_v126: + name = "v126" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.012 + std = 0.482 + data = None + + +class Program_weight_tensor_meta_v128: + name = "v128" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.018 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v130: + name = "v130" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.046 + data = None + + +class Program_weight_tensor_meta_v132: + name = "v132" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -40.390 + std = 3.518 + data = None + + +class Program_weight_tensor_meta_v134: + name = "v134" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v136: + name = "v136" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.130 + std = 0.250 + data = None + + +class Program_weight_tensor_meta_v138: + name = "v138" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.580 + std = 0.097 + data = None + + +class Program_weight_tensor_meta_v140: + name = "v140" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.200 + std = 1.217 + data = None + + +class Program_weight_tensor_meta_v142: + name = "v142" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 31.269 + std = 2.720 + data = None + + +class Program_weight_tensor_meta_v144: + name = "v144" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.319 + std = 0.136 + data = None + + +class Program_weight_tensor_meta_v146: + name = "v146" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.076 + std = 0.344 + data = None + + +class Program_weight_tensor_meta_v148: + name = "v148" + shape = [512, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.023 + std = 0.044 + data = None + + +class Program_weight_tensor_meta_v150: + name = "v150" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.041 + data = None + + +class Program_weight_tensor_meta_v152: + name = "v152" + shape = [512, 256, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.048 + data = None + + +class Program_weight_tensor_meta_v154: + name = "v154" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.973 + std = 0.717 + data = None + + +class Program_weight_tensor_meta_v156: + name = "v156" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 40.412 + std = 2.406 + data = None + + +class Program_weight_tensor_meta_v158: + name = "v158" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.976 + std = 0.169 + data = None + + +class Program_weight_tensor_meta_v160: + name = "v160" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.327 + std = 0.080 + data = None + + +class Program_weight_tensor_meta_v162: + name = "v162" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -19.917 + std = 1.532 + data = None + + +class Program_weight_tensor_meta_v164: + name = "v164" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v166: + name = "v166" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.472 + std = 0.364 + data = None + + +class Program_weight_tensor_meta_v168: + name = "v168" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.425 + std = 0.131 + data = None + + +class Program_weight_tensor_meta_v170: + name = "v170" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.046 + std = 0.648 + data = None + + +class Program_weight_tensor_meta_v172: + name = "v172" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 10.253 + std = 0.739 + data = None + + +class Program_weight_tensor_meta_v174: + name = "v174" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.889 + std = 0.160 + data = None + + +class Program_weight_tensor_meta_v176: + name = "v176" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.020 + std = 0.392 + data = None + + +class Program_weight_tensor_meta_v178: + name = "v178" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.025 + std = 0.040 + data = None + + +class Program_weight_tensor_meta_v180: + name = "v180" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.039 + data = None + + +class Program_weight_tensor_meta_v182: + name = "v182" + shape = [1, 64, 56, 56] + dtype = "torch.float32" + device = "cuda:0" + mean = 4.477 + std = 21.060 + data = None + + +class Program_weight_tensor_meta_v184: + name = "v184" + shape = [1, 64, 56, 56] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.106 + std = 1.056 + data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json new file mode 100644 index 000000000..6d11cb0b7 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json @@ -0,0 +1,7 @@ +{ + "framework": "torch", + "num_devices_required": 1, + "num_nodes_required": 1, + "dynamic": false, + "model_name": "resnet18_2" +} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_meta.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/input_meta.py rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_meta.py diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_tensor_constraints.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/input_tensor_constraints.py rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_tensor_constraints.py diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py new file mode 100644 index 000000000..21f8dd7b3 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py @@ -0,0 +1,285 @@ +import torch + + +class GraphModule(torch.nn.Module): + def forward( + self, + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + x_10, + x_15, + ): + x_15 += x_10 + x_16 = x_15 + x_15 = x_10 = None + x_17 = torch.nn.functional.relu(x_16, inplace=True) + x_16 = None + x_18 = torch.conv2d( + x_17, + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, + None, + (2, 2), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ = None + x_19 = torch.nn.functional.batch_norm( + x_18, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_18 = ( + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ = None + x_20 = torch.nn.functional.relu(x_19, inplace=True) + x_19 = None + x_21 = torch.conv2d( + x_20, + l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_20 = l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ = None + x_22 = torch.nn.functional.batch_norm( + x_21, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_21 = ( + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ = None + input_1 = torch.conv2d( + x_17, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, + None, + (2, 2), + (0, 0), + (1, 1), + 1, + ) + x_17 = l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) + input_2 = torch.nn.functional.batch_norm( + input_1, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + input_1 = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) + x_22 += input_2 + x_23 = x_22 + x_22 = input_2 = None + x_24 = torch.nn.functional.relu(x_23, inplace=True) + x_23 = None + x_25 = torch.conv2d( + x_24, + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ = None + x_26 = torch.nn.functional.batch_norm( + x_25, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_25 = ( + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ = None + x_27 = torch.nn.functional.relu(x_26, inplace=True) + x_26 = None + x_28 = torch.conv2d( + x_27, + l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_27 = l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ = None + x_29 = torch.nn.functional.batch_norm( + x_28, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_28 = ( + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ = None + return ( + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + x_24, + x_29, + ) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py new file mode 100644 index 000000000..9d30f7464 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py @@ -0,0 +1,788 @@ +class Program_weight_tensor_meta_v0: + name = "v0" + shape = [1000] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.514 + std = 0.066 + data = None + + +class Program_weight_tensor_meta_v2: + name = "v2" + shape = [1000, 512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.046 + std = 0.055 + data = None + + +class Program_weight_tensor_meta_v4: + name = "v4" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -4.751 + std = 2.747 + data = None + + +class Program_weight_tensor_meta_v6: + name = "v6" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v8: + name = "v8" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.565 + std = 0.247 + data = None + + +class Program_weight_tensor_meta_v10: + name = "v10" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.496 + std = 0.084 + data = None + + +class Program_weight_tensor_meta_v12: + name = "v12" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.645 + std = 1.716 + data = None + + +class Program_weight_tensor_meta_v14: + name = "v14" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 58.118 + std = 5.192 + data = None + + +class Program_weight_tensor_meta_v16: + name = "v16" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.747 + std = 0.232 + data = None + + +class Program_weight_tensor_meta_v18: + name = "v18" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.160 + std = 0.355 + data = None + + +class Program_weight_tensor_meta_v20: + name = "v20" + shape = [128, 64, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.052 + data = None + + +class Program_weight_tensor_meta_v22: + name = "v22" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.000 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v24: + name = "v24" + shape = [128, 64, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.010 + std = 0.054 + data = None + + +class Program_weight_tensor_meta_v26: + name = "v26" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.302 + std = 1.015 + data = None + + +class Program_weight_tensor_meta_v28: + name = "v28" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 17.628 + std = 1.354 + data = None + + +class Program_weight_tensor_meta_v30: + name = "v30" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.518 + std = 0.234 + data = None + + +class Program_weight_tensor_meta_v32: + name = "v32" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.106 + std = 0.106 + data = None + + +class Program_weight_tensor_meta_v34: + name = "v34" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -13.357 + std = 2.853 + data = None + + +class Program_weight_tensor_meta_v36: + name = "v36" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v38: + name = "v38" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.293 + std = 0.257 + data = None + + +class Program_weight_tensor_meta_v40: + name = "v40" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.617 + std = 0.102 + data = None + + +class Program_weight_tensor_meta_v42: + name = "v42" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.066 + std = 0.746 + data = None + + +class Program_weight_tensor_meta_v44: + name = "v44" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = 34.897 + std = 4.158 + data = None + + +class Program_weight_tensor_meta_v46: + name = "v46" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.954 + std = 0.453 + data = None + + +class Program_weight_tensor_meta_v48: + name = "v48" + shape = [128] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.058 + std = 0.477 + data = None + + +class Program_weight_tensor_meta_v50: + name = "v50" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.051 + data = None + + +class Program_weight_tensor_meta_v52: + name = "v52" + shape = [128, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v54: + name = "v54" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -11.724 + std = 2.568 + data = None + + +class Program_weight_tensor_meta_v56: + name = "v56" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v58: + name = "v58" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.309 + std = 0.249 + data = None + + +class Program_weight_tensor_meta_v60: + name = "v60" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.956 + std = 0.105 + data = None + + +class Program_weight_tensor_meta_v62: + name = "v62" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.036 + std = 2.517 + data = None + + +class Program_weight_tensor_meta_v64: + name = "v64" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v66: + name = "v66" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.161 + std = 0.255 + data = None + + +class Program_weight_tensor_meta_v68: + name = "v68" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.180 + std = 0.421 + data = None + + +class Program_weight_tensor_meta_v70: + name = "v70" + shape = [256, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.049 + data = None + + +class Program_weight_tensor_meta_v72: + name = "v72" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v74: + name = "v74" + shape = [256, 128, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.008 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v76: + name = "v76" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.276 + std = 0.731 + data = None + + +class Program_weight_tensor_meta_v78: + name = "v78" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 33.667 + std = 3.078 + data = None + + +class Program_weight_tensor_meta_v80: + name = "v80" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.133 + std = 0.196 + data = None + + +class Program_weight_tensor_meta_v82: + name = "v82" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.080 + std = 0.093 + data = None + + +class Program_weight_tensor_meta_v84: + name = "v84" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -18.895 + std = 2.806 + data = None + + +class Program_weight_tensor_meta_v86: + name = "v86" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v88: + name = "v88" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.732 + std = 0.294 + data = None + + +class Program_weight_tensor_meta_v90: + name = "v90" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.591 + std = 0.122 + data = None + + +class Program_weight_tensor_meta_v92: + name = "v92" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.197 + std = 1.055 + data = None + + +class Program_weight_tensor_meta_v94: + name = "v94" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 36.599 + std = 1.702 + data = None + + +class Program_weight_tensor_meta_v96: + name = "v96" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.189 + std = 0.297 + data = None + + +class Program_weight_tensor_meta_v98: + name = "v98" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.012 + std = 0.482 + data = None + + +class Program_weight_tensor_meta_v100: + name = "v100" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.018 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v102: + name = "v102" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.046 + data = None + + +class Program_weight_tensor_meta_v104: + name = "v104" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -40.390 + std = 3.518 + data = None + + +class Program_weight_tensor_meta_v106: + name = "v106" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v108: + name = "v108" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.130 + std = 0.250 + data = None + + +class Program_weight_tensor_meta_v110: + name = "v110" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.580 + std = 0.097 + data = None + + +class Program_weight_tensor_meta_v112: + name = "v112" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.200 + std = 1.217 + data = None + + +class Program_weight_tensor_meta_v114: + name = "v114" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 31.269 + std = 2.720 + data = None + + +class Program_weight_tensor_meta_v116: + name = "v116" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.319 + std = 0.136 + data = None + + +class Program_weight_tensor_meta_v118: + name = "v118" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.076 + std = 0.344 + data = None + + +class Program_weight_tensor_meta_v120: + name = "v120" + shape = [512, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.023 + std = 0.044 + data = None + + +class Program_weight_tensor_meta_v122: + name = "v122" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.041 + data = None + + +class Program_weight_tensor_meta_v124: + name = "v124" + shape = [512, 256, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.048 + data = None + + +class Program_weight_tensor_meta_v126: + name = "v126" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.973 + std = 0.717 + data = None + + +class Program_weight_tensor_meta_v128: + name = "v128" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 40.412 + std = 2.406 + data = None + + +class Program_weight_tensor_meta_v130: + name = "v130" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.976 + std = 0.169 + data = None + + +class Program_weight_tensor_meta_v132: + name = "v132" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.327 + std = 0.080 + data = None + + +class Program_weight_tensor_meta_v134: + name = "v134" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -19.917 + std = 1.532 + data = None + + +class Program_weight_tensor_meta_v136: + name = "v136" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v138: + name = "v138" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.472 + std = 0.364 + data = None + + +class Program_weight_tensor_meta_v140: + name = "v140" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.425 + std = 0.131 + data = None + + +class Program_weight_tensor_meta_v142: + name = "v142" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.046 + std = 0.648 + data = None + + +class Program_weight_tensor_meta_v144: + name = "v144" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 10.253 + std = 0.739 + data = None + + +class Program_weight_tensor_meta_v146: + name = "v146" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.889 + std = 0.160 + data = None + + +class Program_weight_tensor_meta_v148: + name = "v148" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.020 + std = 0.392 + data = None + + +class Program_weight_tensor_meta_v150: + name = "v150" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.025 + std = 0.040 + data = None + + +class Program_weight_tensor_meta_v152: + name = "v152" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.039 + data = None + + +class Program_weight_tensor_meta_v154: + name = "v154" + shape = [1, 64, 56, 56] + dtype = "torch.float32" + device = "cuda:0" + mean = 3.870 + std = 20.981 + data = None + + +class Program_weight_tensor_meta_v156: + name = "v156" + shape = [1, 64, 56, 56] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.377 + std = 0.367 + data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json new file mode 100644 index 000000000..26eeadd84 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json @@ -0,0 +1,7 @@ +{ + "framework": "torch", + "num_devices_required": 1, + "num_nodes_required": 1, + "dynamic": false, + "model_name": "resnet18_3" +} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_meta.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN/graph_net.json rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_meta.py diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_tensor_constraints.py similarity index 100% rename from todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/graph_net.json rename to todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_tensor_constraints.py diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py new file mode 100644 index 000000000..f2efffc7f --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py @@ -0,0 +1,365 @@ +import torch + + +class GraphModule(torch.nn.Module): + def forward( + self, + l_l_self_modules_fc_parameters_bias_, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + x_24, + x_29, + ): + x_29 += x_24 + x_30 = x_29 + x_29 = x_24 = None + x_31 = torch.nn.functional.relu(x_30, inplace=True) + x_30 = None + x_32 = torch.conv2d( + x_31, + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, + None, + (2, 2), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ = None + x_33 = torch.nn.functional.batch_norm( + x_32, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_32 = ( + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ = None + x_34 = torch.nn.functional.relu(x_33, inplace=True) + x_33 = None + x_35 = torch.conv2d( + x_34, + l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_34 = l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ = None + x_36 = torch.nn.functional.batch_norm( + x_35, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_35 = ( + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ = None + input_3 = torch.conv2d( + x_31, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, + None, + (2, 2), + (0, 0), + (1, 1), + 1, + ) + x_31 = l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) + input_4 = torch.nn.functional.batch_norm( + input_3, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + input_3 = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) + x_36 += input_4 + x_37 = x_36 + x_36 = input_4 = None + x_38 = torch.nn.functional.relu(x_37, inplace=True) + x_37 = None + x_39 = torch.conv2d( + x_38, + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ = None + x_40 = torch.nn.functional.batch_norm( + x_39, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_39 = ( + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ = None + x_41 = torch.nn.functional.relu(x_40, inplace=True) + x_40 = None + x_42 = torch.conv2d( + x_41, + l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_41 = l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ = None + x_43 = torch.nn.functional.batch_norm( + x_42, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_42 = ( + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ = None + x_43 += x_38 + x_44 = x_43 + x_43 = x_38 = None + x_45 = torch.nn.functional.relu(x_44, inplace=True) + x_44 = None + x_46 = torch.conv2d( + x_45, + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, + None, + (2, 2), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ = None + x_47 = torch.nn.functional.batch_norm( + x_46, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_46 = ( + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ = None + x_48 = torch.nn.functional.relu(x_47, inplace=True) + x_47 = None + x_49 = torch.conv2d( + x_48, + l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_48 = l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ = None + x_50 = torch.nn.functional.batch_norm( + x_49, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_49 = ( + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ = None + input_5 = torch.conv2d( + x_45, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, + None, + (2, 2), + (0, 0), + (1, 1), + 1, + ) + x_45 = l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) + input_6 = torch.nn.functional.batch_norm( + input_5, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, + l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + input_5 = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) + x_50 += input_6 + x_51 = x_50 + x_50 = input_6 = None + x_52 = torch.nn.functional.relu(x_51, inplace=True) + x_51 = None + x_53 = torch.conv2d( + x_52, + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ = None + x_54 = torch.nn.functional.batch_norm( + x_53, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_53 = ( + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ + ) = ( + l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ + ) = ( + l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ + ) = l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ = None + x_55 = torch.nn.functional.relu(x_54, inplace=True) + x_54 = None + x_56 = torch.conv2d( + x_55, + l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, + None, + (1, 1), + (1, 1), + (1, 1), + 1, + ) + x_55 = l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ = None + x_57 = torch.nn.functional.batch_norm( + x_56, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, + False, + 0.1, + 1e-05, + ) + x_56 = ( + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ + ) = ( + l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ + ) = ( + l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ + ) = l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ = None + x_57 += x_52 + x_58 = x_57 + x_57 = x_52 = None + x_59 = torch.nn.functional.relu(x_58, inplace=True) + x_58 = None + x_60 = torch.nn.functional.adaptive_avg_pool2d(x_59, 1) + x_59 = None + x_61 = x_60.flatten(1, -1) + x_60 = None + x_62 = torch._C._nn.linear( + x_61, + l_l_self_modules_fc_parameters_weight_, + l_l_self_modules_fc_parameters_bias_, + ) + x_61 = ( + l_l_self_modules_fc_parameters_weight_ + ) = l_l_self_modules_fc_parameters_bias_ = None + return (x_62,) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py new file mode 100644 index 000000000..abb4db842 --- /dev/null +++ b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py @@ -0,0 +1,538 @@ +class Program_weight_tensor_meta_v0: + name = "v0" + shape = [1000] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.514 + std = 0.066 + data = None + + +class Program_weight_tensor_meta_v2: + name = "v2" + shape = [1000, 512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.046 + std = 0.055 + data = None + + +class Program_weight_tensor_meta_v4: + name = "v4" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -11.724 + std = 2.568 + data = None + + +class Program_weight_tensor_meta_v6: + name = "v6" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v8: + name = "v8" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.309 + std = 0.249 + data = None + + +class Program_weight_tensor_meta_v10: + name = "v10" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.956 + std = 0.105 + data = None + + +class Program_weight_tensor_meta_v12: + name = "v12" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.036 + std = 2.517 + data = None + + +class Program_weight_tensor_meta_v14: + name = "v14" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v16: + name = "v16" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.161 + std = 0.255 + data = None + + +class Program_weight_tensor_meta_v18: + name = "v18" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.180 + std = 0.421 + data = None + + +class Program_weight_tensor_meta_v20: + name = "v20" + shape = [256, 128, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.012 + std = 0.049 + data = None + + +class Program_weight_tensor_meta_v22: + name = "v22" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.001 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v24: + name = "v24" + shape = [256, 128, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.008 + std = 0.050 + data = None + + +class Program_weight_tensor_meta_v26: + name = "v26" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.276 + std = 0.731 + data = None + + +class Program_weight_tensor_meta_v28: + name = "v28" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 33.667 + std = 3.078 + data = None + + +class Program_weight_tensor_meta_v30: + name = "v30" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.133 + std = 0.196 + data = None + + +class Program_weight_tensor_meta_v32: + name = "v32" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.080 + std = 0.093 + data = None + + +class Program_weight_tensor_meta_v34: + name = "v34" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -18.895 + std = 2.806 + data = None + + +class Program_weight_tensor_meta_v36: + name = "v36" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v38: + name = "v38" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.732 + std = 0.294 + data = None + + +class Program_weight_tensor_meta_v40: + name = "v40" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.591 + std = 0.122 + data = None + + +class Program_weight_tensor_meta_v42: + name = "v42" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.197 + std = 1.055 + data = None + + +class Program_weight_tensor_meta_v44: + name = "v44" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 36.599 + std = 1.702 + data = None + + +class Program_weight_tensor_meta_v46: + name = "v46" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.189 + std = 0.297 + data = None + + +class Program_weight_tensor_meta_v48: + name = "v48" + shape = [256] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.012 + std = 0.482 + data = None + + +class Program_weight_tensor_meta_v50: + name = "v50" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.018 + std = 0.047 + data = None + + +class Program_weight_tensor_meta_v52: + name = "v52" + shape = [256, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.001 + std = 0.046 + data = None + + +class Program_weight_tensor_meta_v54: + name = "v54" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -40.390 + std = 3.518 + data = None + + +class Program_weight_tensor_meta_v56: + name = "v56" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v58: + name = "v58" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.130 + std = 0.250 + data = None + + +class Program_weight_tensor_meta_v60: + name = "v60" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.580 + std = 0.097 + data = None + + +class Program_weight_tensor_meta_v62: + name = "v62" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.200 + std = 1.217 + data = None + + +class Program_weight_tensor_meta_v64: + name = "v64" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 31.269 + std = 2.720 + data = None + + +class Program_weight_tensor_meta_v66: + name = "v66" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.319 + std = 0.136 + data = None + + +class Program_weight_tensor_meta_v68: + name = "v68" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.076 + std = 0.344 + data = None + + +class Program_weight_tensor_meta_v70: + name = "v70" + shape = [512, 256, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.023 + std = 0.044 + data = None + + +class Program_weight_tensor_meta_v72: + name = "v72" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.041 + data = None + + +class Program_weight_tensor_meta_v74: + name = "v74" + shape = [512, 256, 1, 1] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.016 + std = 0.048 + data = None + + +class Program_weight_tensor_meta_v76: + name = "v76" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -3.973 + std = 0.717 + data = None + + +class Program_weight_tensor_meta_v78: + name = "v78" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 40.412 + std = 2.406 + data = None + + +class Program_weight_tensor_meta_v80: + name = "v80" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.976 + std = 0.169 + data = None + + +class Program_weight_tensor_meta_v82: + name = "v82" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.327 + std = 0.080 + data = None + + +class Program_weight_tensor_meta_v84: + name = "v84" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -19.917 + std = 1.532 + data = None + + +class Program_weight_tensor_meta_v86: + name = "v86" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 100.000 + std = 0.000 + data = None + + +class Program_weight_tensor_meta_v88: + name = "v88" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -2.472 + std = 0.364 + data = None + + +class Program_weight_tensor_meta_v90: + name = "v90" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 1.425 + std = 0.131 + data = None + + +class Program_weight_tensor_meta_v92: + name = "v92" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.046 + std = 0.648 + data = None + + +class Program_weight_tensor_meta_v94: + name = "v94" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 10.253 + std = 0.739 + data = None + + +class Program_weight_tensor_meta_v96: + name = "v96" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = -1.889 + std = 0.160 + data = None + + +class Program_weight_tensor_meta_v98: + name = "v98" + shape = [512] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.020 + std = 0.392 + data = None + + +class Program_weight_tensor_meta_v100: + name = "v100" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.025 + std = 0.040 + data = None + + +class Program_weight_tensor_meta_v102: + name = "v102" + shape = [512, 512, 3, 3] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.000 + std = 0.039 + data = None + + +class Program_weight_tensor_meta_v104: + name = "v104" + shape = [1, 128, 28, 28] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.798 + std = 1.595 + data = None + + +class Program_weight_tensor_meta_v106: + name = "v106" + shape = [1, 128, 28, 28] + dtype = "torch.float32" + device = "cuda:0" + mean = -0.950 + std = 0.456 + data = None diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/graph_hash.txt b/todo_works/range_decomposer_validator/test/simple_CNN/graph_hash.txt deleted file mode 100644 index 042fac7a8..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN/graph_hash.txt +++ /dev/null @@ -1 +0,0 @@ -c595a90bd71adf88efb78451fc9209bc31b574510f7b0dfae00c544b7cca97ca \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/model.py b/todo_works/range_decomposer_validator/test/simple_CNN/model.py deleted file mode 100644 index ca8cf4d43..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN/model.py +++ /dev/null @@ -1,92 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - L_x_: torch.Tensor, - L_self_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_conv1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_conv2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_fc1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_fc1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_fc2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_fc2_parameters_bias_: torch.nn.parameter.Parameter, - ): - l_x_ = L_x_ - l_self_modules_conv1_parameters_weight_ = ( - L_self_modules_conv1_parameters_weight_ - ) - l_self_modules_conv1_parameters_bias_ = L_self_modules_conv1_parameters_bias_ - l_self_modules_conv2_parameters_weight_ = ( - L_self_modules_conv2_parameters_weight_ - ) - l_self_modules_conv2_parameters_bias_ = L_self_modules_conv2_parameters_bias_ - l_self_modules_fc1_parameters_weight_ = L_self_modules_fc1_parameters_weight_ - l_self_modules_fc1_parameters_bias_ = L_self_modules_fc1_parameters_bias_ - l_self_modules_fc2_parameters_weight_ = L_self_modules_fc2_parameters_weight_ - l_self_modules_fc2_parameters_bias_ = L_self_modules_fc2_parameters_bias_ - - # --- Subgraph 0 --- - # conv1 -> relu -> pool1 - input_1 = torch.conv2d( - l_x_, - l_self_modules_conv1_parameters_weight_, - l_self_modules_conv1_parameters_bias_, - (1, 1), # stride - (1, 1), # padding - (1, 1), # dilation - 1, # groups - ) - l_x_ = ( - l_self_modules_conv1_parameters_weight_ - ) = l_self_modules_conv1_parameters_bias_ = None - input_2 = torch.nn.functional.relu(input_1, inplace=True) - input_1 = None - input_3 = torch.nn.functional.max_pool2d(input_2, 2, 2, 0, 1, ceil_mode=False) - input_2 = None - - # --- Subgraph 1 --- - # conv2 -> relu -> pool2 - input_4 = torch.conv2d( - input_3, - l_self_modules_conv2_parameters_weight_, - l_self_modules_conv2_parameters_bias_, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - input_3 = ( - l_self_modules_conv2_parameters_weight_ - ) = l_self_modules_conv2_parameters_bias_ = None - input_5 = torch.nn.functional.relu(input_4, inplace=True) - input_4 = None - input_6 = torch.nn.functional.max_pool2d(input_5, 2, 2, 0, 1, ceil_mode=False) - input_5 = None - - # --- Subgraph 2 --- - # flatten -> fc1 -> relu -> fc2 - input_7 = torch.flatten(input_6, 1) - input_6 = None - input_8 = torch._C._nn.linear( - input_7, - l_self_modules_fc1_parameters_weight_, - l_self_modules_fc1_parameters_bias_, - ) - input_7 = ( - l_self_modules_fc1_parameters_weight_ - ) = l_self_modules_fc1_parameters_bias_ = None - input_9 = torch.nn.functional.relu(input_8, inplace=True) - input_8 = None - input_10 = torch._C._nn.linear( - input_9, - l_self_modules_fc2_parameters_weight_, - l_self_modules_fc2_parameters_bias_, - ) - input_9 = ( - l_self_modules_fc2_parameters_weight_ - ) = l_self_modules_fc2_parameters_bias_ = None - - return (input_10,) diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/weight_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN/weight_meta.py deleted file mode 100644 index 8c38d90e1..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN/weight_meta.py +++ /dev/null @@ -1,88 +0,0 @@ -class Program_weight_tensor_meta_L_x_: - name = "L_x_" - shape = [1, 1, 28, 28] # Batch size 1, 1 channel, 28x28 image - dtype = "torch.float32" - device = "cuda:0" - mean = 0.130 - std = 0.308 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv1_parameters_weight_: - name = "L_self_modules_conv1_parameters_weight_" - shape = [16, 1, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.108 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv1_parameters_bias_: - name = "L_self_modules_conv1_parameters_bias_" - shape = [16] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.1 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv2_parameters_weight_: - name = "L_self_modules_conv2_parameters_weight_" - shape = [32, 16, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.002 - std = 0.055 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv2_parameters_bias_: - name = "L_self_modules_conv2_parameters_bias_" - shape = [32] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.05 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc1_parameters_weight_: - name = "L_self_modules_fc1_parameters_weight_" - shape = [128, 1568] # 1568 = 32 * 7 * 7 - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.025 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc1_parameters_bias_: - name = "L_self_modules_fc1_parameters_bias_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.02 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc2_parameters_weight_: - name = "L_self_modules_fc2_parameters_weight_" - shape = [10, 128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.088 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc2_parameters_bias_: - name = "L_self_modules_fc2_parameters_bias_" - shape = [10] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.09 - data = None diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/model.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/model.py deleted file mode 100644 index 10b0eda6f..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/model.py +++ /dev/null @@ -1,36 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - L_x_: torch.Tensor, - L_self_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_conv1_parameters_bias_: torch.nn.parameter.Parameter, - ): - l_x_ = L_x_ - l_self_modules_conv1_parameters_weight_ = ( - L_self_modules_conv1_parameters_weight_ - ) - l_self_modules_conv1_parameters_bias_ = L_self_modules_conv1_parameters_bias_ - - # --- Subgraph 0 --- - # conv1 -> relu -> pool1 - input_1 = torch.conv2d( - l_x_, - l_self_modules_conv1_parameters_weight_, - l_self_modules_conv1_parameters_bias_, - (1, 1), # stride - (1, 1), # padding - (1, 1), # dilation - 1, # groups - ) - l_x_ = ( - l_self_modules_conv1_parameters_weight_ - ) = l_self_modules_conv1_parameters_bias_ = None - input_2 = torch.nn.functional.relu(input_1, inplace=True) - input_1 = None - input_3 = torch.nn.functional.max_pool2d(input_2, 2, 2, 0, 1, ceil_mode=False) - input_2 = None - - return (input_3,) diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/weight_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/weight_meta.py deleted file mode 100644 index 8ab978cf3..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/weight_meta.py +++ /dev/null @@ -1,28 +0,0 @@ -class Program_weight_tensor_meta_L_x_: - name = "L_x_" - shape = [1, 1, 28, 28] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.130 - std = 0.308 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv1_parameters_weight_: - name = "L_self_modules_conv1_parameters_weight_" - shape = [16, 1, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.108 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv1_parameters_bias_: - name = "L_self_modules_conv1_parameters_bias_" - shape = [16] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.1 - data = None diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/graph_net.json b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/graph_net.json deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/model.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/model.py deleted file mode 100644 index 69149201e..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/model.py +++ /dev/null @@ -1,35 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - input_3: torch.Tensor, # Output of subgraph_0 - L_self_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_conv2_parameters_bias_: torch.nn.parameter.Parameter, - ): - l_self_modules_conv2_parameters_weight_ = ( - L_self_modules_conv2_parameters_weight_ - ) - l_self_modules_conv2_parameters_bias_ = L_self_modules_conv2_parameters_bias_ - - # --- Subgraph 1 --- - # conv2 -> relu -> pool2 - input_4 = torch.conv2d( - input_3, - l_self_modules_conv2_parameters_weight_, - l_self_modules_conv2_parameters_bias_, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - input_3 = ( - l_self_modules_conv2_parameters_weight_ - ) = l_self_modules_conv2_parameters_bias_ = None - input_5 = torch.nn.functional.relu(input_4, inplace=True) - input_4 = None - input_6 = torch.nn.functional.max_pool2d(input_5, 2, 2, 0, 1, ceil_mode=False) - input_5 = None - - return (input_6,) diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/weight_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/weight_meta.py deleted file mode 100644 index a4f9001dd..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/weight_meta.py +++ /dev/null @@ -1,29 +0,0 @@ -# 这是 subgraph_0 的输出，同时也是 subgraph_1 的输入 -class Program_weight_tensor_meta_input_3: - name = "input_3" - shape = [1, 16, 14, 14] # 28x28 经过一次 2x2 池化后变为 14x14 - dtype = "torch.float32" - device = "cuda:0" - mean = None - std = None - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv2_parameters_weight_: - name = "L_self_modules_conv2_parameters_weight_" - shape = [32, 16, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.002 - std = 0.055 - data = None - - -class Program_weight_tensor_meta_L_self_modules_conv2_parameters_bias_: - name = "L_self_modules_conv2_parameters_bias_" - shape = [32] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.05 - data = None diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/graph_net.json b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/graph_net.json deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/model.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/model.py deleted file mode 100644 index bad03c955..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/model.py +++ /dev/null @@ -1,41 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - input_6: torch.Tensor, # Output of subgraph_1 - L_self_modules_fc1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_fc1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_fc2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_fc2_parameters_bias_: torch.nn.parameter.Parameter, - ): - l_self_modules_fc1_parameters_weight_ = L_self_modules_fc1_parameters_weight_ - l_self_modules_fc1_parameters_bias_ = L_self_modules_fc1_parameters_bias_ - l_self_modules_fc2_parameters_weight_ = L_self_modules_fc2_parameters_weight_ - l_self_modules_fc2_parameters_bias_ = L_self_modules_fc2_parameters_bias_ - - # --- Subgraph 2 --- - # flatten -> fc1 -> relu -> fc2 - input_7 = torch.flatten(input_6, 1) - input_6 = None - input_8 = torch._C._nn.linear( - input_7, - l_self_modules_fc1_parameters_weight_, - l_self_modules_fc1_parameters_bias_, - ) - input_7 = ( - l_self_modules_fc1_parameters_weight_ - ) = l_self_modules_fc1_parameters_bias_ = None - input_9 = torch.nn.functional.relu(input_8, inplace=True) - input_8 = None - input_10 = torch._C._nn.linear( - input_9, - l_self_modules_fc2_parameters_weight_, - l_self_modules_fc2_parameters_bias_, - ) - input_9 = ( - l_self_modules_fc2_parameters_weight_ - ) = l_self_modules_fc2_parameters_bias_ = None - - return (input_10,) diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/weight_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/weight_meta.py deleted file mode 100644 index 71ed88e14..000000000 --- a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/weight_meta.py +++ /dev/null @@ -1,49 +0,0 @@ -# 这是 subgraph_1 的输出，同时也是 subgraph_2 的输入 -class Program_weight_tensor_meta_input_6: - name = "input_6" - shape = [1, 32, 7, 7] # 14x14 经过一次 2x2 池化后变为 7x7 - dtype = "torch.float32" - device = "cuda:0" - mean = None - std = None - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc1_parameters_weight_: - name = "L_self_modules_fc1_parameters_weight_" - shape = [128, 1568] # 1568 = 32 * 7 * 7 - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.025 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc1_parameters_bias_: - name = "L_self_modules_fc1_parameters_bias_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.02 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc2_parameters_weight_: - name = "L_self_modules_fc2_parameters_weight_" - shape = [10, 128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.088 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc2_parameters_bias_: - name = "L_self_modules_fc2_parameters_bias_" - shape = [10] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.0 - std = 0.09 - data = None From b1de6a043bf9ebdca369f42f5dbc77374cd6bea3 Mon Sep 17 00:00:00 2001 From: fangfangssj <1135470306@qq.com> Date: Tue, 11 Nov 2025 16:36:21 +0800 Subject: [PATCH 3/4] fix --- .../test/chain_naive_graph_decomposer_test.sh | 9 +- graph_net/test/decomposer_validator_test.sh | 37 +- .../range_decomposer_validator_backend.py | 74 +- .../range_decomposer_validator/__init__.py | 0 .../test/resnet18/graph_hash.txt | 1 - .../test/resnet18/graph_net.json | 7 - .../test/resnet18/input_meta.py | 0 .../test/resnet18/input_tensor_constraints.py | 0 .../test/resnet18/model.py | 977 --------------- .../test/resnet18/weight_meta.py | 1064 ----------------- .../resnet18_0/graph_net.json | 7 - .../resnet18_0/input_meta.py | 0 .../resnet18_0/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_0/model.py | 277 ----- .../resnet18_0/weight_meta.py | 1028 ---------------- .../resnet18_1/graph_net.json | 7 - .../resnet18_1/input_meta.py | 0 .../resnet18_1/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_1/model.py | 259 ---- .../resnet18_1/weight_meta.py | 928 -------------- .../resnet18_2/graph_net.json | 7 - .../resnet18_2/input_meta.py | 0 .../resnet18_2/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_2/model.py | 285 ----- .../resnet18_2/weight_meta.py | 788 ------------ .../resnet18_3/graph_net.json | 7 - .../resnet18_3/input_meta.py | 0 .../resnet18_3/input_tensor_constraints.py | 0 .../resnet18_decomposed/resnet18_3/model.py | 365 ------ .../resnet18_3/weight_meta.py | 538 --------- 30 files changed, 34 insertions(+), 6631 deletions(-) delete mode 100644 todo_works/range_decomposer_validator/__init__.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt delete mode 100644 todo_works/range_decomposer_validator/test/resnet18/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/resnet18/input_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18/input_tensor_constraints.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18/model.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_tensor_constraints.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_tensor_constraints.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_tensor_constraints.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_meta.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_tensor_constraints.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py delete mode 100644 todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py diff --git a/graph_net/test/chain_naive_graph_decomposer_test.sh b/graph_net/test/chain_naive_graph_decomposer_test.sh index fe6755cba..10ece10e1 100644 --- a/graph_net/test/chain_naive_graph_decomposer_test.sh +++ b/graph_net/test/chain_naive_graph_decomposer_test.sh @@ -4,15 +4,12 @@ GRAPH_NET_ROOT=$(python3 -c "import graph_net; import os; print( os.path.dirname(graph_net.__file__))") # input model path -MODEL_PATH_IN_SAMPLES=/timm/resnet18 -MODEL_NAME=$(basename "$MODEL_PATH_IN_SAMPLES") -OUTPUT_DIR="${NAIVE_DECOMPOSE_WORKSPACE:-$(pwd)/naive_decompose_workspace}" - +MODEL_PATH_IN_SAMPLES=/timm/resnet18 extractor_config_json_str=$(cat < "$FILE_PATH/log.log" 2>&1 -if [ $? -ne 0 ]; then - echo "Error: decomposer_validator execution failed" - echo "Please check the log file: $FILE_PATH/log.log" - exit 1 -fi - python -m graph_net.log2json \ --log-file "$FILE_PATH/log.log" \ --output-dir "$FILE_PATH/JSON_results/" diff --git a/graph_net/torch/backend/range_decomposer_validator_backend.py b/graph_net/torch/backend/range_decomposer_validator_backend.py index 1ece7b689..b89f7a90c 100644 --- a/graph_net/torch/backend/range_decomposer_validator_backend.py +++ b/graph_net/torch/backend/range_decomposer_validator_backend.py @@ -12,54 +12,10 @@ class ComposedModel(nn.Module): def __init__(self, graph: nn.Module, subgraph: List[nn.Module]): super().__init__() self.graph = graph - self.subgraph = nn.ModuleList(subgraph) - self.extract_node = [] - self.graph_model = torch.compile(self.graph, backend=self.extract_compiler) - - def _serialize_arg(self, arg: Any) -> Any: - if isinstance(arg, torch.fx.Node): - return arg.name - if isinstance(arg, (list, tuple)): - return type(arg)(self._serialize_arg(elem) for elem in arg) - if isinstance(arg, dict): - return { - self._serialize_arg(k): self._serialize_arg(v) for k, v in arg.items() - } - return arg - - def _extract_operators_from_graph( - self, gm: nn.Module, example_inputs: List[torch.Tensor] = None - ) -> List[Dict[str, Any]]: - operator_list = [] - for node in gm.graph.nodes: - if node.op in ("call_method", "call_function", "call_module"): - operator_info = { - "op_type": node.op, - "target": node.target, - "kwargs": self._serialize_arg(node.kwargs), - } - - if isinstance(node.target, Callable): - try: - operator_info["target_name"] = node.target.__name__ - except AttributeError: - operator_info["target_name"] = str(node.target) - else: - operator_info["target_name"] = str(node.target) - - operator_list.append(operator_info) - - return operator_list - - def extract_compiler(self, gm: torch.fx.GraphModule, inputs: List[torch.Tensor]): - operator = self._extract_operators_from_graph(gm, inputs) - self.extract_node.append(operator) - return gm.forward + self.subgraphs = nn.ModuleList(subgraph) def forward(self, **kwargs): - self.graph_model(**kwargs) - graph_node_list = list(itertools.chain.from_iterable(self.extract_node)) - self.extract_node = [] + self.graph(**kwargs) subgraph_intput = { key.replace("L", "l_l", 1): value @@ -68,31 +24,11 @@ def forward(self, **kwargs): } output = None - for subgraph_model in self.subgraph: - compiled_model = torch.compile( - subgraph_model, backend=self.extract_compiler - ) - + for subgraph in self.subgraphs: if output is None: - output = compiled_model(**subgraph_intput) + output = subgraph(**subgraph_intput) else: - output = compiled_model(*output) - - subgraph_node_list = list(itertools.chain.from_iterable(self.extract_node)) - self.extract_node = [] - - if graph_node_list != subgraph_node_list: - diff_in_graph = [ - item for item in graph_node_list if item not in subgraph_node_list - ] - diff_in_subgraph = [ - item for item in subgraph_node_list if item not in graph_node_list - ] - - error_msg = f"Subgraph segmentation verification failed\n" - error_msg += f"Nodes in graph but not in subgraph: {diff_in_graph}\n" - error_msg += f"Nodes in subgraph but not in graph: {diff_in_subgraph}" - raise ValueError(error_msg) + output = subgraph(*output) return output diff --git a/todo_works/range_decomposer_validator/__init__.py b/todo_works/range_decomposer_validator/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt b/todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt deleted file mode 100644 index 1e5df26ae..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18/graph_hash.txt +++ /dev/null @@ -1 +0,0 @@ -248d46ebcf5bc02d3e72953ea430b5e18175b0419dbdbcd2479202497f58319d \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18/graph_net.json deleted file mode 100644 index 5a6dada2f..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18/graph_net.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "framework": "torch", - "num_devices_required": 1, - "num_nodes_required": 1, - "source": "timm", - "heuristic_tag": "computer_vision" -} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18/input_meta.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18/input_tensor_constraints.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18/model.py b/todo_works/range_decomposer_validator/test/resnet18/model.py deleted file mode 100644 index 0d741677b..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18/model.py +++ /dev/null @@ -1,977 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - L_self_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - s1: torch.SymInt, - L_x_: torch.Tensor, - L_self_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_: torch.Tensor, - L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_: torch.Tensor, - L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_: torch.Tensor, - L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_: torch.Tensor, - L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_: torch.Tensor, - L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_: torch.Tensor, - L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_: torch.Tensor, - L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_: torch.nn.parameter.Parameter, - L_self_modules_fc_parameters_weight_: torch.nn.parameter.Parameter, - L_self_modules_fc_parameters_bias_: torch.nn.parameter.Parameter, - ): - l_self_modules_conv1_parameters_weight_ = ( - L_self_modules_conv1_parameters_weight_ - ) - l_x_ = L_x_ - l_self_modules_bn1_buffers_running_mean_ = ( - L_self_modules_bn1_buffers_running_mean_ - ) - l_self_modules_bn1_buffers_running_var_ = ( - L_self_modules_bn1_buffers_running_var_ - ) - l_self_modules_bn1_parameters_weight_ = L_self_modules_bn1_parameters_weight_ - l_self_modules_bn1_parameters_bias_ = L_self_modules_bn1_parameters_bias_ - l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ = ( - L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ - ) - l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ = ( - L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ - ) - l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ = ( - L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ - ) - l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ = ( - L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ - ) - l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ = ( - L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ - ) - l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ = ( - L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ - ) - l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ = ( - L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ - ) - l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ = ( - L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ - ) - l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ = ( - L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ - ) - l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ = ( - L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ - ) - l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ = ( - L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ - ) - l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ = ( - L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ - ) - l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ = ( - L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ - ) - l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ = ( - L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ - ) - l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ = ( - L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ - ) - l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ = ( - L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ - ) - l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ = ( - L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ - ) - l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ = ( - L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ - ) - l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ = L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ - l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ - l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ - l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ - l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ = L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ - l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ = ( - L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ - ) - l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ = ( - L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ - ) - l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ = ( - L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ - ) - l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ = ( - L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ - ) - l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ = ( - L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ - ) - l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ = ( - L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ - ) - l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ = ( - L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ - ) - l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ = ( - L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ - ) - l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ = ( - L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ - ) - l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ = ( - L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ - ) - l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ = ( - L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ - ) - l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ = ( - L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ - ) - l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ = L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ - l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ - l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ - l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ - l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ = L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ - l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ = ( - L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ - ) - l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ = ( - L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ - ) - l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ = ( - L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ - ) - l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ = ( - L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ - ) - l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ = ( - L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ - ) - l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ = ( - L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ - ) - l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ = ( - L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ - ) - l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ = ( - L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ - ) - l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ = ( - L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ - ) - l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ = ( - L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ - ) - l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ = ( - L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ - ) - l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ = ( - L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ - ) - l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ = L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ - l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ - l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ - l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ - l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ = L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ - l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ = ( - L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ - ) - l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ = ( - L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ - ) - l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ = ( - L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ - ) - l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ = ( - L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ - ) - l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ = ( - L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ - ) - l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ = ( - L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ - ) - l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ = ( - L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ - ) - l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ = ( - L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ - ) - l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ = ( - L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ - ) - l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ = ( - L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ - ) - l_self_modules_fc_parameters_weight_ = L_self_modules_fc_parameters_weight_ - l_self_modules_fc_parameters_bias_ = L_self_modules_fc_parameters_bias_ - x = torch.conv2d( - l_x_, - l_self_modules_conv1_parameters_weight_, - None, - (2, 2), - (3, 3), - (1, 1), - 1, - ) - l_x_ = l_self_modules_conv1_parameters_weight_ = None - x_1 = torch.nn.functional.batch_norm( - x, - l_self_modules_bn1_buffers_running_mean_, - l_self_modules_bn1_buffers_running_var_, - l_self_modules_bn1_parameters_weight_, - l_self_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x = ( - l_self_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_bn1_parameters_weight_ - ) = l_self_modules_bn1_parameters_bias_ = None - x_2 = torch.nn.functional.relu(x_1, inplace=True) - x_1 = None - x_3 = torch.nn.functional.max_pool2d( - x_2, 3, 2, 1, 1, ceil_mode=False, return_indices=False - ) - x_2 = None - x_4 = torch.conv2d( - x_3, - l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ = None - x_5 = torch.nn.functional.batch_norm( - x_4, - l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_, - l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_, - l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_, - l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_4 = ( - l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ - ) = l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ = None - x_6 = torch.nn.functional.relu(x_5, inplace=True) - x_5 = None - x_7 = torch.conv2d( - x_6, - l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_6 = l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ = None - x_8 = torch.nn.functional.batch_norm( - x_7, - l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, - l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, - l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, - l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_7 = ( - l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ - ) = l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ = None - x_8 += x_3 - x_9 = x_8 - x_8 = x_3 = None - x_10 = torch.nn.functional.relu(x_9, inplace=True) - x_9 = None - x_11 = torch.conv2d( - x_10, - l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ = None - x_12 = torch.nn.functional.batch_norm( - x_11, - l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, - l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, - l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, - l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_11 = ( - l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ - ) = l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ = None - x_13 = torch.nn.functional.relu(x_12, inplace=True) - x_12 = None - x_14 = torch.conv2d( - x_13, - l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_13 = l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ = None - x_15 = torch.nn.functional.batch_norm( - x_14, - l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, - l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, - l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, - l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_14 = ( - l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ - ) = l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ = None - x_15 += x_10 - x_16 = x_15 - x_15 = x_10 = None - x_17 = torch.nn.functional.relu(x_16, inplace=True) - x_16 = None - x_18 = torch.conv2d( - x_17, - l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - None, - (2, 2), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ = None - x_19 = torch.nn.functional.batch_norm( - x_18, - l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_18 = ( - l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ - ) = l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ = None - x_20 = torch.nn.functional.relu(x_19, inplace=True) - x_19 = None - x_21 = torch.conv2d( - x_20, - l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_20 = l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ = None - x_22 = torch.nn.functional.batch_norm( - x_21, - l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_21 = ( - l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ - ) = l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ = None - input_1 = torch.conv2d( - x_17, - l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - None, - (2, 2), - (0, 0), - (1, 1), - 1, - ) - x_17 = l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) - input_2 = torch.nn.functional.batch_norm( - input_1, - l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - input_1 = l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ = l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) - x_22 += input_2 - x_23 = x_22 - x_22 = input_2 = None - x_24 = torch.nn.functional.relu(x_23, inplace=True) - x_23 = None - x_25 = torch.conv2d( - x_24, - l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ = None - x_26 = torch.nn.functional.batch_norm( - x_25, - l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_25 = ( - l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ - ) = l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ = None - x_27 = torch.nn.functional.relu(x_26, inplace=True) - x_26 = None - x_28 = torch.conv2d( - x_27, - l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_27 = l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ = None - x_29 = torch.nn.functional.batch_norm( - x_28, - l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_28 = ( - l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ - ) = l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ = None - x_29 += x_24 - x_30 = x_29 - x_29 = x_24 = None - x_31 = torch.nn.functional.relu(x_30, inplace=True) - x_30 = None - x_32 = torch.conv2d( - x_31, - l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - None, - (2, 2), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ = None - x_33 = torch.nn.functional.batch_norm( - x_32, - l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_32 = ( - l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ - ) = l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ = None - x_34 = torch.nn.functional.relu(x_33, inplace=True) - x_33 = None - x_35 = torch.conv2d( - x_34, - l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_34 = l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ = None - x_36 = torch.nn.functional.batch_norm( - x_35, - l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_35 = ( - l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ - ) = l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ = None - input_3 = torch.conv2d( - x_31, - l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - None, - (2, 2), - (0, 0), - (1, 1), - 1, - ) - x_31 = l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) - input_4 = torch.nn.functional.batch_norm( - input_3, - l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - input_3 = l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ = l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) - x_36 += input_4 - x_37 = x_36 - x_36 = input_4 = None - x_38 = torch.nn.functional.relu(x_37, inplace=True) - x_37 = None - x_39 = torch.conv2d( - x_38, - l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ = None - x_40 = torch.nn.functional.batch_norm( - x_39, - l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_39 = ( - l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ - ) = l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ = None - x_41 = torch.nn.functional.relu(x_40, inplace=True) - x_40 = None - x_42 = torch.conv2d( - x_41, - l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_41 = l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ = None - x_43 = torch.nn.functional.batch_norm( - x_42, - l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_42 = ( - l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ - ) = l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ = None - x_43 += x_38 - x_44 = x_43 - x_43 = x_38 = None - x_45 = torch.nn.functional.relu(x_44, inplace=True) - x_44 = None - x_46 = torch.conv2d( - x_45, - l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - None, - (2, 2), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ = None - x_47 = torch.nn.functional.batch_norm( - x_46, - l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_46 = ( - l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ - ) = l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ = None - x_48 = torch.nn.functional.relu(x_47, inplace=True) - x_47 = None - x_49 = torch.conv2d( - x_48, - l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_48 = l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ = None - x_50 = torch.nn.functional.batch_norm( - x_49, - l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_49 = ( - l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ - ) = l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ = None - input_5 = torch.conv2d( - x_45, - l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - None, - (2, 2), - (0, 0), - (1, 1), - 1, - ) - x_45 = l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) - input_6 = torch.nn.functional.batch_norm( - input_5, - l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - input_5 = l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ = l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) - x_50 += input_6 - x_51 = x_50 - x_50 = input_6 = None - x_52 = torch.nn.functional.relu(x_51, inplace=True) - x_51 = None - x_53 = torch.conv2d( - x_52, - l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ = None - x_54 = torch.nn.functional.batch_norm( - x_53, - l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_53 = ( - l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ - ) = l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ = None - x_55 = torch.nn.functional.relu(x_54, inplace=True) - x_54 = None - x_56 = torch.conv2d( - x_55, - l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_55 = l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ = None - x_57 = torch.nn.functional.batch_norm( - x_56, - l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_56 = ( - l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ - ) = l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ = None - x_57 += x_52 - x_58 = x_57 - x_57 = x_52 = None - x_59 = torch.nn.functional.relu(x_58, inplace=True) - x_58 = None - x_60 = torch.nn.functional.adaptive_avg_pool2d(x_59, 1) - x_59 = None - x_61 = x_60.flatten(1, -1) - x_60 = None - x_62 = torch._C._nn.linear( - x_61, - l_self_modules_fc_parameters_weight_, - l_self_modules_fc_parameters_bias_, - ) - x_61 = ( - l_self_modules_fc_parameters_weight_ - ) = l_self_modules_fc_parameters_bias_ = None - return (x_62,) diff --git a/todo_works/range_decomposer_validator/test/resnet18/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18/weight_meta.py deleted file mode 100644 index 4f1762837..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18/weight_meta.py +++ /dev/null @@ -1,1064 +0,0 @@ -class Program_weight_tensor_meta_L_self_modules_conv1_parameters_weight_: - name = "L_self_modules_conv1_parameters_weight_" - shape = [64, 3, 7, 7] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.235 - data = None - - -class Program_weight_tensor_meta_s1: - name = "s1" - shape = [] - dtype = "torch.int64" - device = "cpu" - mean = None - std = None - data = [4] - - -class Program_weight_tensor_meta_L_x_: - name = "L_x_" - shape = [1, 3, 224, 224] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.225 - std = 1.283 - data = None - - -class Program_weight_tensor_meta_L_self_modules_bn1_buffers_running_mean_: - name = "L_self_modules_bn1_buffers_running_mean_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.003 - std = 0.123 - data = None - - -class Program_weight_tensor_meta_L_self_modules_bn1_buffers_running_var_: - name = "L_self_modules_bn1_buffers_running_var_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 30.655 - std = 90.134 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_bn1_parameters_weight_: - name = "L_self_modules_bn1_parameters_weight_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.285 - std = 0.584 - data = None - - -class Program_weight_tensor_meta_L_self_modules_bn1_parameters_bias_: - name = "L_self_modules_bn1_parameters_bias_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.003 - std = 1.814 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_: - name = "L_self_modules_layer1_modules_0_modules_conv1_parameters_weight_" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.261 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -12.479 - std = 21.250 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 255.163 - std = 382.886 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_: - name = "L_self_modules_layer1_modules_0_modules_bn1_parameters_weight_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.781 - std = 0.500 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_: - name = "L_self_modules_layer1_modules_0_modules_bn1_parameters_bias_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.329 - std = 0.957 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_: - name = "L_self_modules_layer1_modules_0_modules_conv2_parameters_weight_" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.247 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.144 - std = 3.496 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 7.302 - std = 6.209 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_: - name = "L_self_modules_layer1_modules_0_modules_bn2_parameters_weight_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.275 - std = 1.835 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_: - name = "L_self_modules_layer1_modules_0_modules_bn2_parameters_bias_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.776 - std = 1.979 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_: - name = "L_self_modules_layer1_modules_1_modules_conv1_parameters_weight_" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.014 - std = 0.268 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -7.661 - std = 17.322 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 170.317 - std = 247.345 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_: - name = "L_self_modules_layer1_modules_1_modules_bn1_parameters_weight_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.234 - std = 0.433 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_: - name = "L_self_modules_layer1_modules_1_modules_bn1_parameters_bias_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.462 - std = 0.714 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_: - name = "L_self_modules_layer1_modules_1_modules_conv2_parameters_weight_" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.003 - std = 0.260 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.021 - std = 2.934 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 11.941 - std = 4.796 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_: - name = "L_self_modules_layer1_modules_1_modules_bn2_parameters_weight_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.135 - std = 2.538 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_: - name = "L_self_modules_layer1_modules_1_modules_bn2_parameters_bias_" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.356 - std = 1.532 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_: - name = "L_self_modules_layer2_modules_0_modules_conv1_parameters_weight_" - shape = [128, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.260 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -4.639 - std = 12.326 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 330.088 - std = 148.934 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_: - name = "L_self_modules_layer2_modules_0_modules_bn1_parameters_weight_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.498 - std = 0.448 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_: - name = "L_self_modules_layer2_modules_0_modules_bn1_parameters_bias_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.591 - std = 1.256 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_: - name = "L_self_modules_layer2_modules_0_modules_conv2_parameters_weight_" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.250 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.625 - std = 8.374 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 58.237 - std = 28.224 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_: - name = "L_self_modules_layer2_modules_0_modules_bn2_parameters_weight_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.147 - std = 1.901 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_: - name = "L_self_modules_layer2_modules_0_modules_bn2_parameters_bias_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.750 - std = 1.177 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_: - name = "L_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_" - shape = [128, 64, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.271 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_: - name = "L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.265 - std = 5.294 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_: - name = "L_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 17.639 - std = 6.164 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_: - name = "L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.093 - std = 0.581 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_: - name = ( - "L_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_" - ) - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.527 - std = 1.374 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_: - name = "L_self_modules_layer2_modules_1_modules_conv1_parameters_weight_" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.255 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -13.675 - std = 12.174 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 229.209 - std = 140.985 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_: - name = "L_self_modules_layer2_modules_1_modules_bn1_parameters_weight_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.604 - std = 0.540 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_: - name = "L_self_modules_layer2_modules_1_modules_bn1_parameters_bias_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.286 - std = 1.304 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_: - name = "L_self_modules_layer2_modules_1_modules_conv2_parameters_weight_" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.249 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.113 - std = 3.676 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 35.213 - std = 19.076 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_: - name = "L_self_modules_layer2_modules_1_modules_bn2_parameters_weight_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.085 - std = 2.327 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_: - name = "L_self_modules_layer2_modules_1_modules_bn2_parameters_bias_" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.986 - std = 2.047 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_: - name = "L_self_modules_layer3_modules_0_modules_conv1_parameters_weight_" - shape = [256, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.243 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -11.722 - std = 12.927 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 503.389 - std = 202.299 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_: - name = "L_self_modules_layer3_modules_0_modules_bn1_parameters_weight_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.966 - std = 0.549 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_: - name = "L_self_modules_layer3_modules_0_modules_bn1_parameters_bias_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.318 - std = 1.221 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_: - name = "L_self_modules_layer3_modules_0_modules_conv2_parameters_weight_" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.234 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.036 - std = 12.437 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 143.320 - std = 56.891 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_: - name = "L_self_modules_layer3_modules_0_modules_bn2_parameters_weight_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.182 - std = 2.144 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_: - name = "L_self_modules_layer3_modules_0_modules_bn2_parameters_bias_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.152 - std = 1.357 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_: - name = "L_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_" - shape = [256, 128, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.008 - std = 0.252 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_: - name = "L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.227 - std = 3.560 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_: - name = "L_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 33.534 - std = 16.507 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_: - name = "L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.076 - std = 0.477 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_: - name = ( - "L_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_" - ) - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.147 - std = 1.038 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_: - name = "L_self_modules_layer3_modules_1_modules_conv1_parameters_weight_" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.018 - std = 0.233 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -19.051 - std = 14.547 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 367.899 - std = 226.211 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_: - name = "L_self_modules_layer3_modules_1_modules_bn1_parameters_weight_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.596 - std = 0.600 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_: - name = "L_self_modules_layer3_modules_1_modules_bn1_parameters_bias_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.734 - std = 1.526 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_: - name = "L_self_modules_layer3_modules_1_modules_conv2_parameters_weight_" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.229 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.113 - std = 5.289 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 36.753 - std = 9.020 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_: - name = "L_self_modules_layer3_modules_1_modules_bn2_parameters_weight_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.047 - std = 2.414 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_: - name = "L_self_modules_layer3_modules_1_modules_bn2_parameters_bias_" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.184 - std = 1.609 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_: - name = "L_self_modules_layer4_modules_0_modules_conv1_parameters_weight_" - shape = [512, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.023 - std = 0.218 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -40.197 - std = 18.273 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 877.771 - std = 369.567 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_: - name = "L_self_modules_layer4_modules_0_modules_bn1_parameters_weight_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.590 - std = 0.479 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_: - name = "L_self_modules_layer4_modules_0_modules_bn1_parameters_bias_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.139 - std = 1.248 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_: - name = "L_self_modules_layer4_modules_0_modules_conv2_parameters_weight_" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.205 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.093 - std = 5.875 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 31.290 - std = 13.348 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_: - name = "L_self_modules_layer4_modules_0_modules_bn2_parameters_weight_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.036 - std = 1.672 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_: - name = "L_self_modules_layer4_modules_0_modules_bn2_parameters_bias_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.322 - std = 0.698 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_: - name = "L_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_" - shape = [512, 256, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.239 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_: - name = "L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.977 - std = 3.562 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_: - name = "L_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 40.350 - std = 12.568 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_: - name = "L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.331 - std = 0.395 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_: - name = ( - "L_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_" - ) - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.963 - std = 0.855 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_: - name = "L_self_modules_layer4_modules_1_modules_conv1_parameters_weight_" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.025 - std = 0.201 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_: - name = "L_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -19.941 - std = 7.969 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_: - name = "L_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 271.009 - std = 148.261 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_: - name = "L_self_modules_layer4_modules_1_modules_bn1_parameters_weight_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.420 - std = 0.661 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_: - name = "L_self_modules_layer4_modules_1_modules_bn1_parameters_bias_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.482 - std = 1.753 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_: - name = "L_self_modules_layer4_modules_1_modules_conv2_parameters_weight_" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.193 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_: - name = "L_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.020 - std = 3.287 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_: - name = "L_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 10.217 - std = 3.587 - data = None - min_val = 0 - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_: - name = "L_self_modules_layer4_modules_1_modules_bn2_parameters_weight_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.013 - std = 1.906 - data = None - - -class Program_weight_tensor_meta_L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_: - name = "L_self_modules_layer4_modules_1_modules_bn2_parameters_bias_" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.886 - std = 0.808 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc_parameters_weight_: - name = "L_self_modules_fc_parameters_weight_" - shape = [1000, 512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.046 - std = 0.273 - data = None - - -class Program_weight_tensor_meta_L_self_modules_fc_parameters_bias_: - name = "L_self_modules_fc_parameters_bias_" - shape = [1000] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.514 - std = 0.327 - data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json deleted file mode 100644 index 1300cd837..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/graph_net.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "framework": "torch", - "num_devices_required": 1, - "num_nodes_required": 1, - "dynamic": false, - "model_name": "resnet18_0" -} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_meta.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/input_tensor_constraints.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py deleted file mode 100644 index 48c10d00a..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/model.py +++ /dev/null @@ -1,277 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - l_l_self_modules_bn1_buffers_running_mean_, - l_l_self_modules_bn1_buffers_running_var_, - l_l_self_modules_bn1_parameters_bias_, - l_l_self_modules_bn1_parameters_weight_, - l_l_self_modules_conv1_parameters_weight_, - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - l_l_x_, - ): - x = torch.conv2d( - l_l_x_, - l_l_self_modules_conv1_parameters_weight_, - None, - (2, 2), - (3, 3), - (1, 1), - 1, - ) - l_l_x_ = l_l_self_modules_conv1_parameters_weight_ = None - x_1 = torch.nn.functional.batch_norm( - x, - l_l_self_modules_bn1_buffers_running_mean_, - l_l_self_modules_bn1_buffers_running_var_, - l_l_self_modules_bn1_parameters_weight_, - l_l_self_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x = ( - l_l_self_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_bn1_parameters_weight_ - ) = l_l_self_modules_bn1_parameters_bias_ = None - x_2 = torch.nn.functional.relu(x_1, inplace=True) - x_1 = None - x_3 = torch.nn.functional.max_pool2d( - x_2, 3, 2, 1, 1, ceil_mode=False, return_indices=False - ) - x_2 = None - x_4 = torch.conv2d( - x_3, - l_l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer1_modules_0_modules_conv1_parameters_weight_ = None - x_5 = torch.nn.functional.batch_norm( - x_4, - l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_4 = ( - l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer1_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer1_modules_0_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer1_modules_0_modules_bn1_parameters_bias_ = None - x_6 = torch.nn.functional.relu(x_5, inplace=True) - x_5 = None - x_7 = torch.conv2d( - x_6, - l_l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_6 = l_l_self_modules_layer1_modules_0_modules_conv2_parameters_weight_ = None - return ( - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - 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a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py deleted file mode 100644 index caa3b2f20..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_0/weight_meta.py +++ /dev/null @@ -1,1028 +0,0 @@ -class Program_weight_tensor_meta_v0: - name = "v0" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.002 - std = 0.024 - data = None - - -class Program_weight_tensor_meta_v2: - name = "v2" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 32.728 - std = 16.008 - data = None - - -class Program_weight_tensor_meta_v4: - name = "v4" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.914 - std = 0.338 - data = None - - -class Program_weight_tensor_meta_v6: - name = "v6" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.287 - std = 0.119 - data = None - - -class Program_weight_tensor_meta_v8: - name = "v8" - shape = [64, 3, 7, 7] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v10: - name = "v10" - shape = [1000] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.514 - std = 0.066 - data = None - - -class Program_weight_tensor_meta_v12: - name = "v12" - shape = [1000, 512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.046 - std = 0.055 - data = None - - -class Program_weight_tensor_meta_v14: - name = "v14" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -11.456 - std = 3.783 - data = None - - -class Program_weight_tensor_meta_v16: - name = "v16" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 99.144 - std = 4.455 - data = None - - -class Program_weight_tensor_meta_v18: - name = "v18" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.385 - std = 0.208 - data = None - - -class Program_weight_tensor_meta_v20: - name = "v20" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.788 - std = 0.105 - data = None - - -class Program_weight_tensor_meta_v22: - name = "v22" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.134 - std = 0.580 - data = None - - -class Program_weight_tensor_meta_v24: - name = "v24" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 7.212 - std = 1.287 - data = None - - -class Program_weight_tensor_meta_v26: - name = "v26" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.756 - std = 0.372 - data = None - - -class Program_weight_tensor_meta_v28: - name = "v28" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.258 - std = 0.399 - data = None - - -class Program_weight_tensor_meta_v30: - name = "v30" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.052 - data = None - - -class Program_weight_tensor_meta_v32: - name = "v32" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.049 - data = None - - -class Program_weight_tensor_meta_v34: - name = "v34" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -8.395 - std = 3.176 - data = None - - -class Program_weight_tensor_meta_v36: - name = "v36" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 96.830 - std = 12.050 - data = None - - -class Program_weight_tensor_meta_v38: - name = "v38" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.463 - std = 0.130 - data = None - - -class Program_weight_tensor_meta_v40: - name = "v40" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.228 - std = 0.094 - data = None - - -class Program_weight_tensor_meta_v42: - name = "v42" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.023 - std = 0.519 - data = None - - -class Program_weight_tensor_meta_v44: - name = "v44" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 11.859 - std = 1.057 - data = None - - -class Program_weight_tensor_meta_v46: - name = "v46" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.376 - std = 0.298 - data = None - - -class Program_weight_tensor_meta_v48: - name = "v48" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.127 - std = 0.538 - data = None - - -class Program_weight_tensor_meta_v50: - name = "v50" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.014 - std = 0.054 - data = None - - -class Program_weight_tensor_meta_v52: - name = "v52" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.003 - std = 0.052 - data = None - - -class Program_weight_tensor_meta_v54: - name = "v54" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -4.751 - std = 2.747 - data = None - - -class Program_weight_tensor_meta_v56: - name = "v56" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v58: - name = "v58" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.565 - std = 0.247 - data = None - - -class Program_weight_tensor_meta_v60: - name = "v60" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.496 - std = 0.084 - data = None - - -class Program_weight_tensor_meta_v62: - name = "v62" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.645 - std = 1.716 - data = None - - -class Program_weight_tensor_meta_v64: - name = "v64" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 58.118 - std = 5.192 - data = None - - -class Program_weight_tensor_meta_v66: - name = "v66" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.747 - std = 0.232 - data = None - - -class Program_weight_tensor_meta_v68: - name = "v68" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.160 - std = 0.355 - data = None - - -class Program_weight_tensor_meta_v70: - name = "v70" - shape = [128, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.052 - data = None - - -class Program_weight_tensor_meta_v72: - name = "v72" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v74: - name = "v74" - shape = [128, 64, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.054 - data = None - - -class Program_weight_tensor_meta_v76: - name = "v76" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.302 - std = 1.015 - data = None - - -class Program_weight_tensor_meta_v78: - name = "v78" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 17.628 - std = 1.354 - data = None - - -class Program_weight_tensor_meta_v80: - name = "v80" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.518 - std = 0.234 - data = None - - -class Program_weight_tensor_meta_v82: - name = "v82" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.106 - std = 0.106 - data = None - - -class Program_weight_tensor_meta_v84: - name = "v84" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -13.357 - std = 2.853 - data = None - - -class Program_weight_tensor_meta_v86: - name = "v86" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v88: - name = "v88" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.293 - std = 0.257 - data = None - - -class Program_weight_tensor_meta_v90: - name = "v90" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.617 - std = 0.102 - data = None - - -class Program_weight_tensor_meta_v92: - name = "v92" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.066 - std = 0.746 - data = None - - -class Program_weight_tensor_meta_v94: - name = "v94" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 34.897 - std = 4.158 - data = None - - -class Program_weight_tensor_meta_v96: - name = "v96" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.954 - std = 0.453 - data = None - - -class Program_weight_tensor_meta_v98: - name = "v98" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.058 - std = 0.477 - data = None - - -class Program_weight_tensor_meta_v100: - name = "v100" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.051 - data = None - - -class Program_weight_tensor_meta_v102: - name = "v102" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v104: - name = "v104" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -11.724 - std = 2.568 - data = None - - -class Program_weight_tensor_meta_v106: - name = "v106" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v108: - name = "v108" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.309 - std = 0.249 - data = None - - -class Program_weight_tensor_meta_v110: - name = "v110" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.956 - std = 0.105 - data = None - - -class Program_weight_tensor_meta_v112: - name = "v112" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.036 - std = 2.517 - data = None - - -class Program_weight_tensor_meta_v114: - name = "v114" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v116: - name = "v116" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.161 - std = 0.255 - data = None - - -class Program_weight_tensor_meta_v118: - name = "v118" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.180 - std = 0.421 - data = None - - -class Program_weight_tensor_meta_v120: - name = "v120" - shape = [256, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.049 - data = None - - -class Program_weight_tensor_meta_v122: - name = "v122" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v124: - name = "v124" - shape = [256, 128, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.008 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v126: - name = "v126" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.276 - std = 0.731 - data = None - - -class Program_weight_tensor_meta_v128: - name = "v128" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 33.667 - std = 3.078 - data = None - - -class Program_weight_tensor_meta_v130: - name = "v130" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.133 - std = 0.196 - data = None - - -class Program_weight_tensor_meta_v132: - name = "v132" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.080 - std = 0.093 - data = None - - -class Program_weight_tensor_meta_v134: - name = "v134" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -18.895 - std = 2.806 - data = None - - -class Program_weight_tensor_meta_v136: - name = "v136" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v138: - name = "v138" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.732 - std = 0.294 - data = None - - -class Program_weight_tensor_meta_v140: - name = "v140" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.591 - std = 0.122 - data = None - - -class Program_weight_tensor_meta_v142: - name = "v142" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.197 - std = 1.055 - data = None - - -class Program_weight_tensor_meta_v144: - name = "v144" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 36.599 - std = 1.702 - data = None - - -class Program_weight_tensor_meta_v146: - name = "v146" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.189 - std = 0.297 - data = None - - -class Program_weight_tensor_meta_v148: - name = "v148" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.012 - std = 0.482 - data = None - - -class Program_weight_tensor_meta_v150: - name = "v150" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.018 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v152: - name = "v152" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.046 - data = None - - -class Program_weight_tensor_meta_v154: - name = "v154" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -40.390 - std = 3.518 - data = None - - -class Program_weight_tensor_meta_v156: - name = "v156" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v158: - name = "v158" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.130 - std = 0.250 - data = None - - -class Program_weight_tensor_meta_v160: - name = "v160" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.580 - std = 0.097 - data = None - - -class Program_weight_tensor_meta_v162: - name = "v162" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.200 - std = 1.217 - data = None - - -class Program_weight_tensor_meta_v164: - name = "v164" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 31.269 - std = 2.720 - data = None - - -class Program_weight_tensor_meta_v166: - name = "v166" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.319 - std = 0.136 - data = None - - -class Program_weight_tensor_meta_v168: - name = "v168" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.076 - std = 0.344 - data = None - - -class Program_weight_tensor_meta_v170: - name = "v170" - shape = [512, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.023 - std = 0.044 - data = None - - -class Program_weight_tensor_meta_v172: - name = "v172" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.041 - data = None - - -class Program_weight_tensor_meta_v174: - name = "v174" - shape = [512, 256, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.048 - data = None - - -class Program_weight_tensor_meta_v176: - name = "v176" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.973 - std = 0.717 - data = None - - -class Program_weight_tensor_meta_v178: - name = "v178" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 40.412 - std = 2.406 - data = None - - -class Program_weight_tensor_meta_v180: - name = "v180" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.976 - std = 0.169 - data = None - - -class Program_weight_tensor_meta_v182: - name = "v182" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.327 - std = 0.080 - data = None - - -class Program_weight_tensor_meta_v184: - name = "v184" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -19.917 - std = 1.532 - data = None - - -class Program_weight_tensor_meta_v186: - name = "v186" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v188: - name = "v188" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.472 - std = 0.364 - data = None - - -class Program_weight_tensor_meta_v190: - name = "v190" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.425 - std = 0.131 - data = None - - -class Program_weight_tensor_meta_v192: - name = "v192" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.046 - std = 0.648 - data = None - - -class Program_weight_tensor_meta_v194: - name = "v194" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 10.253 - std = 0.739 - data = None - - -class Program_weight_tensor_meta_v196: - name = "v196" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.889 - std = 0.160 - data = None - - -class Program_weight_tensor_meta_v198: - name = "v198" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.020 - std = 0.392 - data = None - - -class Program_weight_tensor_meta_v200: - name = "v200" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.025 - std = 0.040 - data = None - - -class Program_weight_tensor_meta_v202: - name = "v202" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.039 - data = None - - -class Program_weight_tensor_meta_v204: - name = "v204" - shape = [1, 3, 224, 224] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.224 - std = 0.255 - data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json deleted file mode 100644 index 380168032..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/graph_net.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "framework": "torch", - "num_devices_required": 1, - "num_nodes_required": 1, - "dynamic": false, - "model_name": "resnet18_1" -} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_meta.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/input_tensor_constraints.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py deleted file mode 100644 index d545f143d..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/model.py +++ /dev/null @@ -1,259 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - x_3, - x_7, - ): - x_8 = torch.nn.functional.batch_norm( - x_7, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_7 = ( - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer1_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer1_modules_0_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer1_modules_0_modules_bn2_parameters_bias_ = None - x_8 += x_3 - x_9 = x_8 - x_8 = x_3 = None - x_10 = torch.nn.functional.relu(x_9, inplace=True) - x_9 = None - x_11 = torch.conv2d( - x_10, - l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer1_modules_1_modules_conv1_parameters_weight_ = None - x_12 = torch.nn.functional.batch_norm( - x_11, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_11 = ( - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer1_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer1_modules_1_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer1_modules_1_modules_bn1_parameters_bias_ = None - x_13 = torch.nn.functional.relu(x_12, inplace=True) - x_12 = None - x_14 = torch.conv2d( - x_13, - l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_13 = l_l_self_modules_layer1_modules_1_modules_conv2_parameters_weight_ = None - x_15 = torch.nn.functional.batch_norm( - x_14, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_14 = ( - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer1_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer1_modules_1_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer1_modules_1_modules_bn2_parameters_bias_ = None - return ( - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - x_10, - x_15, - ) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py deleted file mode 100644 index b1a3a373e..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_1/weight_meta.py +++ /dev/null @@ -1,928 +0,0 @@ -class Program_weight_tensor_meta_v0: - name = "v0" - shape = [1000] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.514 - std = 0.066 - data = None - - -class Program_weight_tensor_meta_v2: - name = "v2" - shape = [1000, 512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.046 - std = 0.055 - data = None - - -class Program_weight_tensor_meta_v4: - name = "v4" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.134 - std = 0.580 - data = None - - -class Program_weight_tensor_meta_v6: - name = "v6" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 7.212 - std = 1.287 - data = None - - -class Program_weight_tensor_meta_v8: - name = "v8" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.756 - std = 0.372 - data = None - - -class Program_weight_tensor_meta_v10: - name = "v10" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.258 - std = 0.399 - data = None - - -class Program_weight_tensor_meta_v12: - name = "v12" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -8.395 - std = 3.176 - data = None - - -class Program_weight_tensor_meta_v14: - name = "v14" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 96.830 - std = 12.050 - data = None - - -class Program_weight_tensor_meta_v16: - name = "v16" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.463 - std = 0.130 - data = None - - -class Program_weight_tensor_meta_v18: - name = "v18" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.228 - std = 0.094 - data = None - - -class Program_weight_tensor_meta_v20: - name = "v20" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.023 - std = 0.519 - data = None - - -class Program_weight_tensor_meta_v22: - name = "v22" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = 11.859 - std = 1.057 - data = None - - -class Program_weight_tensor_meta_v24: - name = "v24" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.376 - std = 0.298 - data = None - - -class Program_weight_tensor_meta_v26: - name = "v26" - shape = [64] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.127 - std = 0.538 - data = None - - -class Program_weight_tensor_meta_v28: - name = "v28" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.014 - std = 0.054 - data = None - - -class Program_weight_tensor_meta_v30: - name = "v30" - shape = [64, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.003 - std = 0.052 - data = None - - -class Program_weight_tensor_meta_v32: - name = "v32" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -4.751 - std = 2.747 - data = None - - -class Program_weight_tensor_meta_v34: - name = "v34" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v36: - name = "v36" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.565 - std = 0.247 - data = None - - -class Program_weight_tensor_meta_v38: - name = "v38" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.496 - std = 0.084 - data = None - - -class Program_weight_tensor_meta_v40: - name = "v40" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.645 - std = 1.716 - data = None - - -class Program_weight_tensor_meta_v42: - name = "v42" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 58.118 - std = 5.192 - data = None - - -class Program_weight_tensor_meta_v44: - name = "v44" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.747 - std = 0.232 - data = None - - -class Program_weight_tensor_meta_v46: - name = "v46" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.160 - std = 0.355 - data = None - - -class Program_weight_tensor_meta_v48: - name = "v48" - shape = [128, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.052 - data = None - - -class Program_weight_tensor_meta_v50: - name = "v50" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v52: - name = "v52" - shape = [128, 64, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.054 - data = None - - -class Program_weight_tensor_meta_v54: - name = "v54" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.302 - std = 1.015 - data = None - - -class Program_weight_tensor_meta_v56: - name = "v56" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 17.628 - std = 1.354 - data = None - - -class Program_weight_tensor_meta_v58: - name = "v58" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.518 - std = 0.234 - data = None - - -class Program_weight_tensor_meta_v60: - name = "v60" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.106 - std = 0.106 - data = None - - -class Program_weight_tensor_meta_v62: - name = "v62" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -13.357 - std = 2.853 - data = None - - -class Program_weight_tensor_meta_v64: - name = "v64" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v66: - name = "v66" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.293 - std = 0.257 - data = None - - -class Program_weight_tensor_meta_v68: - name = "v68" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.617 - std = 0.102 - data = None - - -class Program_weight_tensor_meta_v70: - name = "v70" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.066 - std = 0.746 - data = None - - -class Program_weight_tensor_meta_v72: - name = "v72" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 34.897 - std = 4.158 - data = None - - -class Program_weight_tensor_meta_v74: - name = "v74" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.954 - std = 0.453 - data = None - - -class Program_weight_tensor_meta_v76: - name = "v76" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.058 - std = 0.477 - data = None - - -class Program_weight_tensor_meta_v78: - name = "v78" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.051 - data = None - - -class Program_weight_tensor_meta_v80: - name = "v80" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v82: - name = "v82" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -11.724 - std = 2.568 - data = None - - -class Program_weight_tensor_meta_v84: - name = "v84" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v86: - name = "v86" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.309 - std = 0.249 - data = None - - -class Program_weight_tensor_meta_v88: - name = "v88" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.956 - std = 0.105 - data = None - - -class Program_weight_tensor_meta_v90: - name = "v90" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.036 - std = 2.517 - data = None - - -class Program_weight_tensor_meta_v92: - name = "v92" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v94: - name = "v94" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.161 - std = 0.255 - data = None - - -class Program_weight_tensor_meta_v96: - name = "v96" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.180 - std = 0.421 - data = None - - -class Program_weight_tensor_meta_v98: - name = "v98" - shape = [256, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.049 - data = None - - -class Program_weight_tensor_meta_v100: - name = "v100" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v102: - name = "v102" - shape = [256, 128, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.008 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v104: - name = "v104" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.276 - std = 0.731 - data = None - - -class Program_weight_tensor_meta_v106: - name = "v106" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 33.667 - std = 3.078 - data = None - - -class Program_weight_tensor_meta_v108: - name = "v108" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.133 - std = 0.196 - data = None - - -class Program_weight_tensor_meta_v110: - name = "v110" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.080 - std = 0.093 - data = None - - -class Program_weight_tensor_meta_v112: - name = "v112" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -18.895 - std = 2.806 - data = None - - -class Program_weight_tensor_meta_v114: - name = "v114" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v116: - name = "v116" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.732 - std = 0.294 - data = None - - -class Program_weight_tensor_meta_v118: - name = "v118" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.591 - std = 0.122 - data = None - - -class Program_weight_tensor_meta_v120: - name = "v120" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.197 - std = 1.055 - data = None - - -class Program_weight_tensor_meta_v122: - name = "v122" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 36.599 - std = 1.702 - data = None - - -class Program_weight_tensor_meta_v124: - name = "v124" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.189 - std = 0.297 - data = None - - -class Program_weight_tensor_meta_v126: - name = "v126" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.012 - std = 0.482 - data = None - - -class Program_weight_tensor_meta_v128: - name = "v128" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.018 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v130: - name = "v130" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.046 - data = None - - -class Program_weight_tensor_meta_v132: - name = "v132" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -40.390 - std = 3.518 - data = None - - -class Program_weight_tensor_meta_v134: - name = "v134" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v136: - name = "v136" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.130 - std = 0.250 - data = None - - -class Program_weight_tensor_meta_v138: - name = "v138" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.580 - std = 0.097 - data = None - - -class Program_weight_tensor_meta_v140: - name = "v140" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.200 - std = 1.217 - data = None - - -class Program_weight_tensor_meta_v142: - name = "v142" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 31.269 - std = 2.720 - data = None - - -class Program_weight_tensor_meta_v144: - name = "v144" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.319 - std = 0.136 - data = None - - -class Program_weight_tensor_meta_v146: - name = "v146" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.076 - std = 0.344 - data = None - - -class Program_weight_tensor_meta_v148: - name = "v148" - shape = [512, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.023 - std = 0.044 - data = None - - -class Program_weight_tensor_meta_v150: - name = "v150" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.041 - data = None - - -class Program_weight_tensor_meta_v152: - name = "v152" - shape = [512, 256, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.048 - data = None - - -class Program_weight_tensor_meta_v154: - name = "v154" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.973 - std = 0.717 - data = None - - -class Program_weight_tensor_meta_v156: - name = "v156" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 40.412 - std = 2.406 - data = None - - -class Program_weight_tensor_meta_v158: - name = "v158" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.976 - std = 0.169 - data = None - - -class Program_weight_tensor_meta_v160: - name = "v160" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.327 - std = 0.080 - data = None - - -class Program_weight_tensor_meta_v162: - name = "v162" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -19.917 - std = 1.532 - data = None - - -class Program_weight_tensor_meta_v164: - name = "v164" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v166: - name = "v166" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.472 - std = 0.364 - data = None - - -class Program_weight_tensor_meta_v168: - name = "v168" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.425 - std = 0.131 - data = None - - -class Program_weight_tensor_meta_v170: - name = "v170" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.046 - std = 0.648 - data = None - - -class Program_weight_tensor_meta_v172: - name = "v172" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 10.253 - std = 0.739 - data = None - - -class Program_weight_tensor_meta_v174: - name = "v174" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.889 - std = 0.160 - data = None - - -class Program_weight_tensor_meta_v176: - name = "v176" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.020 - std = 0.392 - data = None - - -class Program_weight_tensor_meta_v178: - name = "v178" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.025 - std = 0.040 - data = None - - -class Program_weight_tensor_meta_v180: - name = "v180" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.039 - data = None - - -class Program_weight_tensor_meta_v182: - name = "v182" - shape = [1, 64, 56, 56] - dtype = "torch.float32" - device = "cuda:0" - mean = 4.477 - std = 21.060 - data = None - - -class Program_weight_tensor_meta_v184: - name = "v184" - shape = [1, 64, 56, 56] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.106 - std = 1.056 - data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json deleted file mode 100644 index 6d11cb0b7..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/graph_net.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "framework": "torch", - "num_devices_required": 1, - "num_nodes_required": 1, - "dynamic": false, - "model_name": "resnet18_2" -} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_meta.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/input_tensor_constraints.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py deleted file mode 100644 index 21f8dd7b3..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/model.py +++ /dev/null @@ -1,285 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - x_10, - x_15, - ): - x_15 += x_10 - x_16 = x_15 - x_15 = x_10 = None - x_17 = torch.nn.functional.relu(x_16, inplace=True) - x_16 = None - x_18 = torch.conv2d( - x_17, - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_, - None, - (2, 2), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer2_modules_0_modules_conv1_parameters_weight_ = None - x_19 = torch.nn.functional.batch_norm( - x_18, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_18 = ( - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer2_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer2_modules_0_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer2_modules_0_modules_bn1_parameters_bias_ = None - x_20 = torch.nn.functional.relu(x_19, inplace=True) - x_19 = None - x_21 = torch.conv2d( - x_20, - l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_20 = l_l_self_modules_layer2_modules_0_modules_conv2_parameters_weight_ = None - x_22 = torch.nn.functional.batch_norm( - x_21, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_21 = ( - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer2_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer2_modules_0_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer2_modules_0_modules_bn2_parameters_bias_ = None - input_1 = torch.conv2d( - x_17, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_, - None, - (2, 2), - (0, 0), - (1, 1), - 1, - ) - x_17 = l_l_self_modules_layer2_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) - input_2 = torch.nn.functional.batch_norm( - input_1, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - input_1 = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_weight_ = l_l_self_modules_layer2_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) - x_22 += input_2 - x_23 = x_22 - x_22 = input_2 = None - x_24 = torch.nn.functional.relu(x_23, inplace=True) - x_23 = None - x_25 = torch.conv2d( - x_24, - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer2_modules_1_modules_conv1_parameters_weight_ = None - x_26 = torch.nn.functional.batch_norm( - x_25, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_25 = ( - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer2_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer2_modules_1_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer2_modules_1_modules_bn1_parameters_bias_ = None - x_27 = torch.nn.functional.relu(x_26, inplace=True) - x_26 = None - x_28 = torch.conv2d( - x_27, - l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_27 = l_l_self_modules_layer2_modules_1_modules_conv2_parameters_weight_ = None - x_29 = torch.nn.functional.batch_norm( - x_28, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_28 = ( - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer2_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer2_modules_1_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer2_modules_1_modules_bn2_parameters_bias_ = None - return ( - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - x_24, - x_29, - ) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py deleted file mode 100644 index 9d30f7464..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_2/weight_meta.py +++ /dev/null @@ -1,788 +0,0 @@ -class Program_weight_tensor_meta_v0: - name = "v0" - shape = [1000] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.514 - std = 0.066 - data = None - - -class Program_weight_tensor_meta_v2: - name = "v2" - shape = [1000, 512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.046 - std = 0.055 - data = None - - -class Program_weight_tensor_meta_v4: - name = "v4" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -4.751 - std = 2.747 - data = None - - -class Program_weight_tensor_meta_v6: - name = "v6" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v8: - name = "v8" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.565 - std = 0.247 - data = None - - -class Program_weight_tensor_meta_v10: - name = "v10" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.496 - std = 0.084 - data = None - - -class Program_weight_tensor_meta_v12: - name = "v12" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.645 - std = 1.716 - data = None - - -class Program_weight_tensor_meta_v14: - name = "v14" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 58.118 - std = 5.192 - data = None - - -class Program_weight_tensor_meta_v16: - name = "v16" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.747 - std = 0.232 - data = None - - -class Program_weight_tensor_meta_v18: - name = "v18" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.160 - std = 0.355 - data = None - - -class Program_weight_tensor_meta_v20: - name = "v20" - shape = [128, 64, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.052 - data = None - - -class Program_weight_tensor_meta_v22: - name = "v22" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.000 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v24: - name = "v24" - shape = [128, 64, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.010 - std = 0.054 - data = None - - -class Program_weight_tensor_meta_v26: - name = "v26" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.302 - std = 1.015 - data = None - - -class Program_weight_tensor_meta_v28: - name = "v28" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 17.628 - std = 1.354 - data = None - - -class Program_weight_tensor_meta_v30: - name = "v30" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.518 - std = 0.234 - data = None - - -class Program_weight_tensor_meta_v32: - name = "v32" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.106 - std = 0.106 - data = None - - -class Program_weight_tensor_meta_v34: - name = "v34" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -13.357 - std = 2.853 - data = None - - -class Program_weight_tensor_meta_v36: - name = "v36" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v38: - name = "v38" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.293 - std = 0.257 - data = None - - -class Program_weight_tensor_meta_v40: - name = "v40" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.617 - std = 0.102 - data = None - - -class Program_weight_tensor_meta_v42: - name = "v42" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.066 - std = 0.746 - data = None - - -class Program_weight_tensor_meta_v44: - name = "v44" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = 34.897 - std = 4.158 - data = None - - -class Program_weight_tensor_meta_v46: - name = "v46" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.954 - std = 0.453 - data = None - - -class Program_weight_tensor_meta_v48: - name = "v48" - shape = [128] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.058 - std = 0.477 - data = None - - -class Program_weight_tensor_meta_v50: - name = "v50" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.051 - data = None - - -class Program_weight_tensor_meta_v52: - name = "v52" - shape = [128, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v54: - name = "v54" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -11.724 - std = 2.568 - data = None - - -class Program_weight_tensor_meta_v56: - name = "v56" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v58: - name = "v58" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.309 - std = 0.249 - data = None - - -class Program_weight_tensor_meta_v60: - name = "v60" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.956 - std = 0.105 - data = None - - -class Program_weight_tensor_meta_v62: - name = "v62" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.036 - std = 2.517 - data = None - - -class Program_weight_tensor_meta_v64: - name = "v64" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v66: - name = "v66" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.161 - std = 0.255 - data = None - - -class Program_weight_tensor_meta_v68: - name = "v68" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.180 - std = 0.421 - data = None - - -class Program_weight_tensor_meta_v70: - name = "v70" - shape = [256, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.049 - data = None - - -class Program_weight_tensor_meta_v72: - name = "v72" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v74: - name = "v74" - shape = [256, 128, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.008 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v76: - name = "v76" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.276 - std = 0.731 - data = None - - -class Program_weight_tensor_meta_v78: - name = "v78" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 33.667 - std = 3.078 - data = None - - -class Program_weight_tensor_meta_v80: - name = "v80" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.133 - std = 0.196 - data = None - - -class Program_weight_tensor_meta_v82: - name = "v82" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.080 - std = 0.093 - data = None - - -class Program_weight_tensor_meta_v84: - name = "v84" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -18.895 - std = 2.806 - data = None - - -class Program_weight_tensor_meta_v86: - name = "v86" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v88: - name = "v88" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.732 - std = 0.294 - data = None - - -class Program_weight_tensor_meta_v90: - name = "v90" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.591 - std = 0.122 - data = None - - -class Program_weight_tensor_meta_v92: - name = "v92" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.197 - std = 1.055 - data = None - - -class Program_weight_tensor_meta_v94: - name = "v94" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 36.599 - std = 1.702 - data = None - - -class Program_weight_tensor_meta_v96: - name = "v96" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.189 - std = 0.297 - data = None - - -class Program_weight_tensor_meta_v98: - name = "v98" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.012 - std = 0.482 - data = None - - -class Program_weight_tensor_meta_v100: - name = "v100" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.018 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v102: - name = "v102" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.046 - data = None - - -class Program_weight_tensor_meta_v104: - name = "v104" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -40.390 - std = 3.518 - data = None - - -class Program_weight_tensor_meta_v106: - name = "v106" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v108: - name = "v108" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.130 - std = 0.250 - data = None - - -class Program_weight_tensor_meta_v110: - name = "v110" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.580 - std = 0.097 - data = None - - -class Program_weight_tensor_meta_v112: - name = "v112" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.200 - std = 1.217 - data = None - - -class Program_weight_tensor_meta_v114: - name = "v114" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 31.269 - std = 2.720 - data = None - - -class Program_weight_tensor_meta_v116: - name = "v116" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.319 - std = 0.136 - data = None - - -class Program_weight_tensor_meta_v118: - name = "v118" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.076 - std = 0.344 - data = None - - -class Program_weight_tensor_meta_v120: - name = "v120" - shape = [512, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.023 - std = 0.044 - data = None - - -class Program_weight_tensor_meta_v122: - name = "v122" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.041 - data = None - - -class Program_weight_tensor_meta_v124: - name = "v124" - shape = [512, 256, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.048 - data = None - - -class Program_weight_tensor_meta_v126: - name = "v126" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.973 - std = 0.717 - data = None - - -class Program_weight_tensor_meta_v128: - name = "v128" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 40.412 - std = 2.406 - data = None - - -class Program_weight_tensor_meta_v130: - name = "v130" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.976 - std = 0.169 - data = None - - -class Program_weight_tensor_meta_v132: - name = "v132" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.327 - std = 0.080 - data = None - - -class Program_weight_tensor_meta_v134: - name = "v134" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -19.917 - std = 1.532 - data = None - - -class Program_weight_tensor_meta_v136: - name = "v136" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v138: - name = "v138" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.472 - std = 0.364 - data = None - - -class Program_weight_tensor_meta_v140: - name = "v140" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.425 - std = 0.131 - data = None - - -class Program_weight_tensor_meta_v142: - name = "v142" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.046 - std = 0.648 - data = None - - -class Program_weight_tensor_meta_v144: - name = "v144" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 10.253 - std = 0.739 - data = None - - -class Program_weight_tensor_meta_v146: - name = "v146" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.889 - std = 0.160 - data = None - - -class Program_weight_tensor_meta_v148: - name = "v148" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.020 - std = 0.392 - data = None - - -class Program_weight_tensor_meta_v150: - name = "v150" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.025 - std = 0.040 - data = None - - -class Program_weight_tensor_meta_v152: - name = "v152" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.039 - data = None - - -class Program_weight_tensor_meta_v154: - name = "v154" - shape = [1, 64, 56, 56] - dtype = "torch.float32" - device = "cuda:0" - mean = 3.870 - std = 20.981 - data = None - - -class Program_weight_tensor_meta_v156: - name = "v156" - shape = [1, 64, 56, 56] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.377 - std = 0.367 - data = None diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json deleted file mode 100644 index 26eeadd84..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/graph_net.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "framework": "torch", - "num_devices_required": 1, - "num_nodes_required": 1, - "dynamic": false, - "model_name": "resnet18_3" -} \ No newline at end of file diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_meta.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/input_tensor_constraints.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py deleted file mode 100644 index f2efffc7f..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/model.py +++ /dev/null @@ -1,365 +0,0 @@ -import torch - - -class GraphModule(torch.nn.Module): - def forward( - self, - l_l_self_modules_fc_parameters_bias_, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - x_24, - x_29, - ): - x_29 += x_24 - x_30 = x_29 - x_29 = x_24 = None - x_31 = torch.nn.functional.relu(x_30, inplace=True) - x_30 = None - x_32 = torch.conv2d( - x_31, - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_, - None, - (2, 2), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer3_modules_0_modules_conv1_parameters_weight_ = None - x_33 = torch.nn.functional.batch_norm( - x_32, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_32 = ( - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer3_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer3_modules_0_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer3_modules_0_modules_bn1_parameters_bias_ = None - x_34 = torch.nn.functional.relu(x_33, inplace=True) - x_33 = None - x_35 = torch.conv2d( - x_34, - l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_34 = l_l_self_modules_layer3_modules_0_modules_conv2_parameters_weight_ = None - x_36 = torch.nn.functional.batch_norm( - x_35, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_35 = ( - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer3_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer3_modules_0_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer3_modules_0_modules_bn2_parameters_bias_ = None - input_3 = torch.conv2d( - x_31, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_, - None, - (2, 2), - (0, 0), - (1, 1), - 1, - ) - x_31 = l_l_self_modules_layer3_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) - input_4 = torch.nn.functional.batch_norm( - input_3, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - input_3 = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_weight_ = l_l_self_modules_layer3_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) - x_36 += input_4 - x_37 = x_36 - x_36 = input_4 = None - x_38 = torch.nn.functional.relu(x_37, inplace=True) - x_37 = None - x_39 = torch.conv2d( - x_38, - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer3_modules_1_modules_conv1_parameters_weight_ = None - x_40 = torch.nn.functional.batch_norm( - x_39, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_39 = ( - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer3_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer3_modules_1_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer3_modules_1_modules_bn1_parameters_bias_ = None - x_41 = torch.nn.functional.relu(x_40, inplace=True) - x_40 = None - x_42 = torch.conv2d( - x_41, - l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_41 = l_l_self_modules_layer3_modules_1_modules_conv2_parameters_weight_ = None - x_43 = torch.nn.functional.batch_norm( - x_42, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_42 = ( - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer3_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer3_modules_1_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer3_modules_1_modules_bn2_parameters_bias_ = None - x_43 += x_38 - x_44 = x_43 - x_43 = x_38 = None - x_45 = torch.nn.functional.relu(x_44, inplace=True) - x_44 = None - x_46 = torch.conv2d( - x_45, - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_, - None, - (2, 2), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer4_modules_0_modules_conv1_parameters_weight_ = None - x_47 = torch.nn.functional.batch_norm( - x_46, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_46 = ( - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer4_modules_0_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer4_modules_0_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer4_modules_0_modules_bn1_parameters_bias_ = None - x_48 = torch.nn.functional.relu(x_47, inplace=True) - x_47 = None - x_49 = torch.conv2d( - x_48, - l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_48 = l_l_self_modules_layer4_modules_0_modules_conv2_parameters_weight_ = None - x_50 = torch.nn.functional.batch_norm( - x_49, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_49 = ( - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer4_modules_0_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer4_modules_0_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer4_modules_0_modules_bn2_parameters_bias_ = None - input_5 = torch.conv2d( - x_45, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_, - None, - (2, 2), - (0, 0), - (1, 1), - 1, - ) - x_45 = l_l_self_modules_layer4_modules_0_modules_downsample_modules_0_parameters_weight_ = (None) - input_6 = torch.nn.functional.batch_norm( - input_5, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_, - l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - input_5 = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_mean_ = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_buffers_running_var_ = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_weight_ = l_l_self_modules_layer4_modules_0_modules_downsample_modules_1_parameters_bias_ = (None) - x_50 += input_6 - x_51 = x_50 - x_50 = input_6 = None - x_52 = torch.nn.functional.relu(x_51, inplace=True) - x_51 = None - x_53 = torch.conv2d( - x_52, - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - l_l_self_modules_layer4_modules_1_modules_conv1_parameters_weight_ = None - x_54 = torch.nn.functional.batch_norm( - x_53, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_53 = ( - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_mean_ - ) = ( - l_l_self_modules_layer4_modules_1_modules_bn1_buffers_running_var_ - ) = ( - l_l_self_modules_layer4_modules_1_modules_bn1_parameters_weight_ - ) = l_l_self_modules_layer4_modules_1_modules_bn1_parameters_bias_ = None - x_55 = torch.nn.functional.relu(x_54, inplace=True) - x_54 = None - x_56 = torch.conv2d( - x_55, - l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_, - None, - (1, 1), - (1, 1), - (1, 1), - 1, - ) - x_55 = l_l_self_modules_layer4_modules_1_modules_conv2_parameters_weight_ = None - x_57 = torch.nn.functional.batch_norm( - x_56, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_, - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_, - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_, - False, - 0.1, - 1e-05, - ) - x_56 = ( - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_mean_ - ) = ( - l_l_self_modules_layer4_modules_1_modules_bn2_buffers_running_var_ - ) = ( - l_l_self_modules_layer4_modules_1_modules_bn2_parameters_weight_ - ) = l_l_self_modules_layer4_modules_1_modules_bn2_parameters_bias_ = None - x_57 += x_52 - x_58 = x_57 - x_57 = x_52 = None - x_59 = torch.nn.functional.relu(x_58, inplace=True) - x_58 = None - x_60 = torch.nn.functional.adaptive_avg_pool2d(x_59, 1) - x_59 = None - x_61 = x_60.flatten(1, -1) - x_60 = None - x_62 = torch._C._nn.linear( - x_61, - l_l_self_modules_fc_parameters_weight_, - l_l_self_modules_fc_parameters_bias_, - ) - x_61 = ( - l_l_self_modules_fc_parameters_weight_ - ) = l_l_self_modules_fc_parameters_bias_ = None - return (x_62,) diff --git a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py b/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py deleted file mode 100644 index abb4db842..000000000 --- a/todo_works/range_decomposer_validator/test/resnet18_decomposed/resnet18_3/weight_meta.py +++ /dev/null @@ -1,538 +0,0 @@ -class Program_weight_tensor_meta_v0: - name = "v0" - shape = [1000] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.514 - std = 0.066 - data = None - - -class Program_weight_tensor_meta_v2: - name = "v2" - shape = [1000, 512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.046 - std = 0.055 - data = None - - -class Program_weight_tensor_meta_v4: - name = "v4" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -11.724 - std = 2.568 - data = None - - -class Program_weight_tensor_meta_v6: - name = "v6" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v8: - name = "v8" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.309 - std = 0.249 - data = None - - -class Program_weight_tensor_meta_v10: - name = "v10" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.956 - std = 0.105 - data = None - - -class Program_weight_tensor_meta_v12: - name = "v12" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.036 - std = 2.517 - data = None - - -class Program_weight_tensor_meta_v14: - name = "v14" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v16: - name = "v16" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.161 - std = 0.255 - data = None - - -class Program_weight_tensor_meta_v18: - name = "v18" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.180 - std = 0.421 - data = None - - -class Program_weight_tensor_meta_v20: - name = "v20" - shape = [256, 128, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.012 - std = 0.049 - data = None - - -class Program_weight_tensor_meta_v22: - name = "v22" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.001 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v24: - name = "v24" - shape = [256, 128, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.008 - std = 0.050 - data = None - - -class Program_weight_tensor_meta_v26: - name = "v26" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.276 - std = 0.731 - data = None - - -class Program_weight_tensor_meta_v28: - name = "v28" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 33.667 - std = 3.078 - data = None - - -class Program_weight_tensor_meta_v30: - name = "v30" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.133 - std = 0.196 - data = None - - -class Program_weight_tensor_meta_v32: - name = "v32" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.080 - std = 0.093 - data = None - - -class Program_weight_tensor_meta_v34: - name = "v34" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -18.895 - std = 2.806 - data = None - - -class Program_weight_tensor_meta_v36: - name = "v36" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v38: - name = "v38" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.732 - std = 0.294 - data = None - - -class Program_weight_tensor_meta_v40: - name = "v40" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.591 - std = 0.122 - data = None - - -class Program_weight_tensor_meta_v42: - name = "v42" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.197 - std = 1.055 - data = None - - -class Program_weight_tensor_meta_v44: - name = "v44" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 36.599 - std = 1.702 - data = None - - -class Program_weight_tensor_meta_v46: - name = "v46" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.189 - std = 0.297 - data = None - - -class Program_weight_tensor_meta_v48: - name = "v48" - shape = [256] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.012 - std = 0.482 - data = None - - -class Program_weight_tensor_meta_v50: - name = "v50" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.018 - std = 0.047 - data = None - - -class Program_weight_tensor_meta_v52: - name = "v52" - shape = [256, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.001 - std = 0.046 - data = None - - -class Program_weight_tensor_meta_v54: - name = "v54" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -40.390 - std = 3.518 - data = None - - -class Program_weight_tensor_meta_v56: - name = "v56" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v58: - name = "v58" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.130 - std = 0.250 - data = None - - -class Program_weight_tensor_meta_v60: - name = "v60" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.580 - std = 0.097 - data = None - - -class Program_weight_tensor_meta_v62: - name = "v62" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.200 - std = 1.217 - data = None - - -class Program_weight_tensor_meta_v64: - name = "v64" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 31.269 - std = 2.720 - data = None - - -class Program_weight_tensor_meta_v66: - name = "v66" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.319 - std = 0.136 - data = None - - -class Program_weight_tensor_meta_v68: - name = "v68" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.076 - std = 0.344 - data = None - - -class Program_weight_tensor_meta_v70: - name = "v70" - shape = [512, 256, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.023 - std = 0.044 - data = None - - -class Program_weight_tensor_meta_v72: - name = "v72" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.041 - data = None - - -class Program_weight_tensor_meta_v74: - name = "v74" - shape = [512, 256, 1, 1] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.016 - std = 0.048 - data = None - - -class Program_weight_tensor_meta_v76: - name = "v76" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -3.973 - std = 0.717 - data = None - - -class Program_weight_tensor_meta_v78: - name = "v78" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 40.412 - std = 2.406 - data = None - - -class Program_weight_tensor_meta_v80: - name = "v80" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.976 - std = 0.169 - data = None - - -class Program_weight_tensor_meta_v82: - name = "v82" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.327 - std = 0.080 - data = None - - -class Program_weight_tensor_meta_v84: - name = "v84" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -19.917 - std = 1.532 - data = None - - -class Program_weight_tensor_meta_v86: - name = "v86" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 100.000 - std = 0.000 - data = None - - -class Program_weight_tensor_meta_v88: - name = "v88" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -2.472 - std = 0.364 - data = None - - -class Program_weight_tensor_meta_v90: - name = "v90" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 1.425 - std = 0.131 - data = None - - -class Program_weight_tensor_meta_v92: - name = "v92" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.046 - std = 0.648 - data = None - - -class Program_weight_tensor_meta_v94: - name = "v94" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 10.253 - std = 0.739 - data = None - - -class Program_weight_tensor_meta_v96: - name = "v96" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = -1.889 - std = 0.160 - data = None - - -class Program_weight_tensor_meta_v98: - name = "v98" - shape = [512] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.020 - std = 0.392 - data = None - - -class Program_weight_tensor_meta_v100: - name = "v100" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.025 - std = 0.040 - data = None - - -class Program_weight_tensor_meta_v102: - name = "v102" - shape = [512, 512, 3, 3] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.000 - std = 0.039 - data = None - - -class Program_weight_tensor_meta_v104: - name = "v104" - shape = [1, 128, 28, 28] - dtype = "torch.float32" - device = "cuda:0" - mean = 0.798 - std = 1.595 - data = None - - -class Program_weight_tensor_meta_v106: - name = "v106" - shape = [1, 128, 28, 28] - dtype = "torch.float32" - device = "cuda:0" - mean = -0.950 - std = 0.456 - data = None From cf1fd643374712b7841e7f23121c4a5b5e11477f Mon Sep 17 00:00:00 2001 From: fangfangssj <1135470306@qq.com> Date: Tue, 11 Nov 2025 16:47:24 +0800 Subject: [PATCH 4/4] remove graph --- .../torch/backend/range_decomposer_validator_backend.py | 8 ++------ 1 file changed, 2 insertions(+), 6 deletions(-) diff --git a/graph_net/torch/backend/range_decomposer_validator_backend.py b/graph_net/torch/backend/range_decomposer_validator_backend.py index b89f7a90c..b1f71cdc7 100644 --- a/graph_net/torch/backend/range_decomposer_validator_backend.py +++ b/graph_net/torch/backend/range_decomposer_validator_backend.py @@ -9,14 +9,11 @@ class ComposedModel(nn.Module): - def __init__(self, graph: nn.Module, subgraph: List[nn.Module]): + def __init__(self, subgraph: List[nn.Module]): super().__init__() - self.graph = graph self.subgraphs = nn.ModuleList(subgraph) def forward(self, **kwargs): - self.graph(**kwargs) - subgraph_intput = { key.replace("L", "l_l", 1): value for key, value in kwargs.items() @@ -61,7 +58,6 @@ def __call__(self, model: torch.nn.Module) -> torch.nn.Module: ) device = model.__class__.__graph_net_device__ - graph_instances = self._load_model_instance(model_dir, device) subgraph_instances = [] for path in subgraph_paths: @@ -72,7 +68,7 @@ def __call__(self, model: torch.nn.Module) -> torch.nn.Module: f"[RangeDecomposerValidatorBackend] Loaded and instantiated '{dir_name}'" ) - composed_model = ComposedModel(graph_instances, subgraph_instances) + composed_model = ComposedModel(subgraph_instances) return composed_model.eval() def synchronize(self):