diff --git a/graph_net/test/chain_naive_graph_decomposer_test.sh b/graph_net/test/chain_naive_graph_decomposer_test.sh
index acdfd3f77..10ece10e1 100644
--- a/graph_net/test/chain_naive_graph_decomposer_test.sh
+++ b/graph_net/test/chain_naive_graph_decomposer_test.sh
@@ -20,4 +20,4 @@ EOF
 EXTRACTOR_CONFIG=$(echo $extractor_config_json_str | base64 -w 0)
 
 mkdir -p /tmp/naive_decompose_workspace
-python3 -m graph_net.torch.single_device_runner --model-path $GRAPH_NET_ROOT/../samples/$MODEL_PATH_IN_SAMPLES --enable-extract True --extract-name resnet18 --dump-graph-hash-key --extractor-config=$EXTRACTOR_CONFIG
+python3 -m graph_net.torch.single_device_runner --model-path $GRAPH_NET_ROOT/../samples/$MODEL_PATH_IN_SAMPLES --enable-extract True --extract-name resnet18 --dump-graph-hash-key --extractor-config=$EXTRACTOR_CONFIG
\ No newline at end of file
diff --git a/graph_net/test/decomposer_validator_test.sh b/graph_net/test/decomposer_validator_test.sh
new file mode 100644
index 000000000..b1d3b01d6
--- /dev/null
+++ b/graph_net/test/decomposer_validator_test.sh
@@ -0,0 +1,51 @@
+#!/bin/bash
+
+GRAPH_NET_ROOT=$(python3 -c "import graph_net; import os; print(os.path.dirname(graph_net.__file__))")
+
+if [ -z "$GRAPH_NET_DECOMPOSE_PATH" ]; then
+    GRAPH_NET_DECOMPOSE_PATH="$(pwd)/graphnet_decompose"
+fi
+
+MODEL_PATH_IN_SAMPLES=/timm/resnet18
+MODEL_NAME=$(basename "$MODEL_PATH_IN_SAMPLES")
+OUTPUT_DIR="${GRAPH_NET_DECOMPOSE_PATH:-$(pwd)}"
+cp -r "$GRAPH_NET_ROOT/../samples/$MODEL_PATH_IN_SAMPLES" "$OUTPUT_DIR/"
+
+extractor_config_json_str=$(cat <<EOF
+{
+    "custom_extractor_path": "$GRAPH_NET_ROOT/torch/naive_graph_decomposer.py",
+    "custom_extractor_config": {
+        "output_dir": "$OUTPUT_DIR/${MODEL_NAME}_decomposed",
+        "split_positions": [8, 16, 32],
+        "group_head_and_tail": true,
+        "chain_style": true
+    }
+}
+EOF
+)
+EXTRACTOR_CONFIG=$(echo $extractor_config_json_str | base64 -w 0)
+python3 -m graph_net.torch.single_device_runner --model-path $GRAPH_NET_ROOT/../samples/$MODEL_PATH_IN_SAMPLES --enable-extract True --extract-name $MODEL_NAME --dump-graph-hash-key --extractor-config=$EXTRACTOR_CONFIG
+
+FILE_PATH=$GRAPH_NET_DECOMPOSE_PATH/decomposer
+mkdir -p "$(dirname "$FILE_PATH/log.log")"
+MODEL_PATH="$GRAPH_NET_DECOMPOSE_PATH/$MODEL_NAME"
+
+python -m graph_net.torch.test_compiler \
+    --model-path $MODEL_PATH \
+    --compiler range_decomposer_validator \
+    --device cuda > "$FILE_PATH/log.log" 2>&1
+
+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: $FILE_PATH/log.log"
+echo "=================================================="
\ No newline at end of file
diff --git a/graph_net/test/naive_graph_decomposer_test.sh b/graph_net/test/naive_graph_decomposer_test.sh
index 2d333266b..f158544e4 100644
--- a/graph_net/test/naive_graph_decomposer_test.sh
+++ b/graph_net/test/naive_graph_decomposer_test.sh
@@ -21,4 +21,4 @@ EOF
 EXTRACTOR_CONFIG=$(echo $extractor_config_json_str | base64 -w 0)
 
 mkdir -p /tmp/naive_decompose_workspace
-python3 -m graph_net.torch.single_device_runner --model-path $GRAPH_NET_ROOT/../samples/$MODEL_PATH_IN_SAMPLES --enable-extract True --extract-name resnet18 --dump-graph-hash-key --extractor-config=$EXTRACTOR_CONFIG
+python3 -m graph_net.torch.single_device_runner --model-path $GRAPH_NET_ROOT/../samples/$MODEL_PATH_IN_SAMPLES --enable-extract True --extract-name resnet18 --dump-graph-hash-key --extractor-config=$EXTRACTOR_CONFIG
\ No newline at end of file
diff --git a/graph_net/torch/backend/range_decomposer_validator_backend.py b/graph_net/torch/backend/range_decomposer_validator_backend.py
new file mode 100644
index 000000000..b1f71cdc7
--- /dev/null
+++ b/graph_net/torch/backend/range_decomposer_validator_backend.py
@@ -0,0 +1,76 @@
+import torch
+import torch.nn as nn
+import os
+import sys
+import inspect
+import importlib.util
+import itertools
+from typing import List, Tuple, Dict, Any, Callable
+
+
+class ComposedModel(nn.Module):
+    def __init__(self, subgraph: List[nn.Module]):
+        super().__init__()
+        self.subgraphs = nn.ModuleList(subgraph)
+
+    def forward(self, **kwargs):
+        subgraph_intput = {
+            key.replace("L", "l_l", 1): value
+            for key, value in kwargs.items()
+            if key.startswith("L")
+        }
+
+        output = None
+        for subgraph in self.subgraphs:
+            if output is None:
+                output = subgraph(**subgraph_intput)
+            else:
+                output = subgraph(*output)
+
+        return output
+
+
+class RangeDecomposerValidatorBackend:
+    def _load_model_instance(self, path: str, device: str) -> torch.nn.Module:
+        class_name = "GraphModule"
+        model_file = os.path.join(path, "model.py")
+
+        spec = importlib.util.spec_from_file_location(class_name, model_file)
+        module = importlib.util.module_from_spec(spec)
+        spec.loader.exec_module(module)
+
+        ModelClass = getattr(module, class_name)
+        instance = ModelClass().to(device)
+        return instance
+
+    def __call__(self, model: torch.nn.Module) -> torch.nn.Module:
+        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 = []
+        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[-1].isdigit():
+                subgraph_paths.append(full_path)
+
+        print(
+            f"[RangeDecomposerValidatorBackend] Found subgraphs: {[os.path.basename(p) for p in subgraph_paths]}"
+        )
+
+        device = model.__class__.__graph_net_device__
+        subgraph_instances = []
+
+        for path in subgraph_paths:
+            instance = self._load_model_instance(path, device)
+            subgraph_instances.append(instance)
+            dir_name = os.path.basename(path)
+            print(
+                f"[RangeDecomposerValidatorBackend] Loaded and instantiated '{dir_name}'"
+            )
+
+        composed_model = ComposedModel(subgraph_instances)
+        return composed_model.eval()
+
+    def synchronize(self):
+        if torch.cuda.is_available():
+            torch.cuda.synchronize()
diff --git a/graph_net/torch/test_compiler.py b/graph_net/torch/test_compiler.py
index f71359f1d..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
@@ -69,6 +69,8 @@ def load_class_from_file(
     exec(compiled_code, module.__dict__)
 
     model_class = getattr(module, class_name, None)
+    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/__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/range_decomposer_validator.py b/todo_works/range_decomposer_validator/range_decomposer_validator.py
deleted file mode 100644
index 18d062526..000000000
--- a/todo_works/range_decomposer_validator/range_decomposer_validator.py
+++ /dev/null
@@ -1,91 +0,0 @@
-import torch
-import torch.nn as nn
-import os
-import sys
-import inspect
-import importlib.util
-from typing import List, Dict
-
-
-class ComposedModel(nn.Module):
-    def __init__(self, submodules: List[nn.Module]):
-        super().__init__()
-        self.submodules = nn.ModuleList(submodules)
-        self.submodule_param_names = [
-            list(inspect.signature(sm.forward).parameters.keys())
-            for sm in self.submodules
-        ]
-
-    def forward(self, **kwargs):
-        current_args = kwargs
-        for i, (sm, param_names) in enumerate(
-            zip(self.submodules, self.submodule_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
-
-            # 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]
-
-            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
-            current_args = outputs[0]
-
-        return (current_args,)
-
-
-class RangeDecomposerValidatorBackend:
-    def _load_model_instance(self, path: str, device: str) -> torch.nn.Module:
-        class_name = "GraphModule"
-        model_file = os.path.join(path, "model.py")
-
-        spec = importlib.util.spec_from_file_location(class_name, model_file)
-        module = importlib.util.module_from_spec(spec)
-        spec.loader.exec_module(module)
-
-        ModelClass = getattr(module, class_name)
-        instance = ModelClass().to(device)
-        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
-        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_"):
-                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
-
-        for path in subgraph_paths:
-            instance = self._load_model_instance(path, device)
-            submodule_instances.append(instance)
-            dir_name = os.path.basename(path)
-            print(
-                f"[RangeDecomposerValidatorBackend] Loaded and instantiated '{dir_name}'"
-            )
-
-        composed_model = ComposedModel(submodule_instances)
-        return composed_model.eval()
-
-    def synchronize(self):
-        if torch.cuda.is_available():
-            torch.cuda.synchronize()
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/graph_net.json b/todo_works/range_decomposer_validator/test/simple_CNN/graph_net.json
deleted file mode 100644
index e69de29bb..000000000
diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/input_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN/input_meta.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/todo_works/range_decomposer_validator/test/simple_CNN/input_tensor_constraints.py b/todo_works/range_decomposer_validator/test/simple_CNN/input_tensor_constraints.py
deleted file mode 100644
index e69de29bb..000000000
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/graph_net.json b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/graph_net.json
deleted file mode 100644
index e69de29bb..000000000
diff --git a/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/input_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_0/input_meta.py
deleted file mode 100644
index e69de29bb..000000000
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/simple_CNN_decomposed/subgraph_0/input_tensor_constraints.py
deleted file mode 100644
index e69de29bb..000000000
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/input_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_1/input_meta.py
deleted file mode 100644
index e69de29bb..000000000
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/simple_CNN_decomposed/subgraph_1/input_tensor_constraints.py
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/input_meta.py b/todo_works/range_decomposer_validator/test/simple_CNN_decomposed/subgraph_2/input_meta.py
deleted file mode 100644
index e69de29bb..000000000
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/simple_CNN_decomposed/subgraph_2/input_tensor_constraints.py
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