[fx] fixed timm tracing result misalignment (#1225)

tests/test_fx/test_tracer/test_timm_model/test_timm_model.py

@@ -11,14 +11,16 @@ from torch.fx import GraphModule
 def trace_and_compare(model_cls, tracer, data, meta_args=None):
     # trace
     model = model_cls()
+
+    # convert to eval for inference
+    # it is important to set it to eval mode before tracing
+    # without this statement, the torch.nn.functional.batch_norm will always be in training mode
+    model.eval()
+
     graph = tracer.trace(root=model, meta_args=meta_args)
     gm = GraphModule(model, graph, model.__class__.__name__)
     gm.recompile()
 
-    # convert to eval for inference
-    model.eval()
-    gm.eval()
-
     # run forward
     with torch.no_grad():
         fx_out = gm(data)
@@ -39,11 +41,14 @@ def test_timm_models_without_control_flow():
     torch.backends.cudnn.deterministic = True
 
     MODEL_LIST = [
-        tm.resnest.resnest50d, tm.beit.beit_base_patch16_224, tm.cait.cait_s24_224, tm.convmixer.convmixer_768_32,
-        tm.efficientnet.efficientnetv2_m, tm.resmlp_12_224, tm.vision_transformer.vit_base_patch16_224
-
-    # results not aligned
-    # tm.deit_base_distilled_patch16_224,
+        tm.resnest.resnest50d,
+        tm.beit.beit_base_patch16_224,
+        tm.cait.cait_s24_224,
+        tm.convmixer.convmixer_768_32,
+        tm.efficientnet.efficientnetv2_m,
+        tm.resmlp_12_224,
+        tm.vision_transformer.vit_base_patch16_224,
+        tm.deit_base_distilled_patch16_224,
     ]
 
     tracer = ColoTracer()
@@ -60,11 +65,11 @@ def test_timm_models_with_control_flow():
     MODEL_LIST_WITH_CONTROL_FLOW = [
         tm.convnext.convnext_base,
         tm.vgg.vgg11,
+        tm.dpn.dpn68,
+        tm.densenet.densenet121,
+        tm.rexnet.rexnet_100,
 
-    # results not aligned
-    # tm.dpn.dpn68,
-    # tm.densenet.densenet121,
-    # tm.rexnet.rexnet_100,
+    # not traceable
     # tm.swin_transformer.swin_base_patch4_window7_224
     ]