delete is_qat, add doc and fix pytest

open-mmlab · Jan 18, 2023 · 6fae8dd · 6fae8dd
1 parent db1acb3
commit 6fae8dd
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Showing 9 changed files with 17 additions and 27 deletions.
diff --git a/configs/quantization/ptq/ptq_openvino_mbv2_8xb32_in1k_calib32xb32.py b/configs/quantization/ptq/ptq_openvino_mbv2_8xb32_in1k_calib32xb32.py
@@ -34,7 +34,6 @@
     float_checkpoint=float_checkpoint,
     quantizer=dict(
         type='mmrazor.OpenVINOQuantizer',
-        is_qat=False,
         global_qconfig=global_qconfig,
         tracer=dict(
             type='mmrazor.CustomTracer',

diff --git a/configs/quantization/ptq/ptq_openvino_resnet18_8xb32_in1k_calib32xb32.py b/configs/quantization/ptq/ptq_openvino_resnet18_8xb32_in1k_calib32xb32.py
@@ -36,7 +36,6 @@
     float_checkpoint=float_checkpoint,
     quantizer=dict(
         type='mmrazor.OpenVINOQuantizer',
-        is_qat=False,
         global_qconfig=global_qconfig,
         tracer=dict(
             type='mmrazor.CustomTracer',

diff --git a/configs/quantization/ptq/ptq_openvino_resnet50_8xb32_in1k_calib32xb32.py b/configs/quantization/ptq/ptq_openvino_resnet50_8xb32_in1k_calib32xb32.py
@@ -36,7 +36,6 @@
     float_checkpoint=float_checkpoint,
     quantizer=dict(
         type='mmrazor.OpenVINOQuantizer',
-        is_qat=False,
         global_qconfig=global_qconfig,
         tracer=dict(
             type='mmrazor.CustomTracer',

diff --git a/configs/quantization/ptq/ptq_openvino_retina_r50_1x_coco_calib32xb32.py b/configs/quantization/ptq/ptq_openvino_retina_r50_1x_coco_calib32xb32.py
@@ -35,7 +35,6 @@
     float_checkpoint=float_checkpoint,
     quantizer=dict(
         type='mmrazor.OpenVINOQuantizer',
-        is_qat=False,
         global_qconfig=global_qconfig,
         tracer=dict(
             type='mmrazor.CustomTracer',

diff --git a/configs/quantization/qat/lsq_openvino_resnet18_8xb32_in1k.py b/configs/quantization/qat/lsq_openvino_resnet18_8xb32_in1k.py
@@ -29,7 +29,6 @@
     float_checkpoint=float_checkpoint,
     quantizer=dict(
         type='mmrazor.OpenVINOQuantizer',
-        is_qat=True,
         global_qconfig=global_qconfig,
         tracer=dict(
             type='mmrazor.CustomTracer',

diff --git a/mmrazor/models/algorithms/quantization/mm_architecture.py b/mmrazor/models/algorithms/quantization/mm_architecture.py
@@ -178,6 +178,9 @@ def _build_qmodels(self, model: BaseModel):
             observed_module = self.quantizer.prepare(model, concrete_args)
             qmodels[mode] = observed_module
 
+        # data_samples can not be None in detectors during prediction.
+        # But we need to make the dummy prediction in _build_qmodels.
+        # It is more convenient to use `tensor` mode.
         is_training = qmodels['tensor'].training
         # Avoid random input changing bn's statistics
         qmodels['tensor'].eval()

diff --git a/mmrazor/models/quantizers/academic_quantizer.py b/mmrazor/models/quantizers/academic_quantizer.py
@@ -104,7 +104,8 @@ def prepare(self, model, concrete_args=None):
         fuse_custom_config = FuseCustomConfig().set_preserved_attributes(
             preserved_attributes)
 
-        self.sync_module_training_mode(graph_module)
+        # set the training modes of all modules to True to `_fuse_fx` correctly
+        self.sync_module_training_mode(graph_module, mode=True)
 
         graph_module = _fuse_fx(
             graph_module=graph_module,

diff --git a/mmrazor/models/quantizers/native_quantizer.py b/mmrazor/models/quantizers/native_quantizer.py
@@ -123,15 +123,21 @@ def __init__(self,
         assert w_mode in self.support_w_modes
         assert a_mode in self.support_a_modes
 
-        self.qconfig_mapping = self.get_qconfig_mapping(no_observer_modules)
+        self.qconfig_mapping = self.gen_qconfig_mapping(
+            self.qconfig, no_observer_modules)
 
         self.backend_config = BackendConfigs[self.backend]
         self.example_inputs = (torch.randn(1, 3, 224, 224), )
 
         self.extra_redundant_fakequants = extra_redundant_fakequants
 
-    def get_qconfig_mapping(self, no_observer_modules):
-        qconfig_mapping = QConfigMapping().set_global(self.qconfig.convert())
+    def gen_qconfig_mapping(self, qconfig, no_observer_modules):
+        """Convert qconfig in config file to `QConfigMapping`.
+
+        `QConfigMapping` is a custom class for mapping from model ops to
+        :class:`torch.ao.quantization.QConfig` s.
+        """
+        qconfig_mapping = QConfigMapping().set_global(qconfig.convert())
 
         if no_observer_modules is not None:
             no_observer_modules = str2class(no_observer_modules)
@@ -197,7 +203,9 @@ def prepare(self, model, concrete_args=None):
         traced_graph = self.tracer.trace(model, concrete_args=concrete_args)
         graph_module = build_graphmodule(model, traced_graph)
 
-        self.sync_module_training_mode(graph_module)
+        # set the training modes of all modules to True to `_fuse_fx` correctly
+        self.sync_module_training_mode(graph_module, mode=True)
+
         graph_module = _fuse_fx(
             graph_module=graph_module,
             is_qat=True,

diff --git a/tests/test_runners/test_quantization_loop.py b/tests/test_runners/test_quantization_loop.py
@@ -39,8 +39,6 @@
     FloatFunctional = get_placeholder('torch>=1.13')
     FXFloatFunctional = get_placeholder('torch>=1.13')
 
-from mmrazor import digit_version
-
 
 class ToyDataset(Dataset):
     METAINFO = dict()  # type: ignore
@@ -68,21 +66,6 @@ def calibrate_step(self, data):
         data = self.data_preprocessor(data, False)
         return self.architecture(**data)
 
-    def swap_ff_with_fxff(self, model):
-        if digit_version(torch.__version__) < digit_version('1.13.0'):
-            self.skipTest('version of torch < 1.13.0')
-
-        modules_to_swap = []
-        for name, module in model.named_children():
-            if isinstance(module, FloatFunctional):
-                modules_to_swap.append(name)
-            else:
-                self.swap_ff_with_fxff(module)
-
-        for name in modules_to_swap:
-            del model._modules[name]
-            model._modules[name] = FXFloatFunctional()
-
     def sync_qparams(self, src_mode):
         pass