update inference ut to support nhwc format (#39551)

* update inference ut to support nhwc format

* update ut and pass OpCompat

* update ut

* update ut

paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.cc

@@ -157,7 +157,7 @@ ConvActivationFusePass::ConvActivationFusePass() {
       // IsStringIn({"NHWC", "NCHW"}) MobileNetV2 has no this attribute
       .AddAttr("data_format")
       .IsOptional()
-      .IsStringIn({"NCHW", "AnyLayout"})
+      .IsStringIn({"NCHW", "NHWC", "AnyLayout"})
       .End();
 
   AddOpCompat(OpCompat("relu"))

paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.cc

@@ -115,7 +115,7 @@ Conv2DTransposeBiasFusePass::Conv2DTransposeBiasFusePass() {
       .IsStringIn({"EXPLICIT", "SAME", "VALID"})
       .End()
       .AddAttr("data_format")
-      .IsStringIn({"NCHW"})
+      .IsStringIn({"NCHW", "NHWC", "AnyLayout"})
       .End();
 
   AddOpCompat(OpCompat("elementwise_add"))
@@ -129,7 +129,7 @@ Conv2DTransposeBiasFusePass::Conv2DTransposeBiasFusePass() {
       .IsTensor()
       .End()
       .AddAttr("axis")
-      .IsIntIn({1})
+      .IsIntIn({1, 3})
       .End();
 }
 

paddle/fluid/framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass.cc

@@ -59,7 +59,7 @@ ConvConcatReLUFusePass::ConvConcatReLUFusePass() {
       .IsType<std::vector<int>>()
       .End()
       .AddAttr("data_format")
-      .IsStringIn({"NCHW"})
+      .IsStringIn({"NCHW", "NHWC", "AnyLayout"})
       .End();
 
   AddOpCompat(OpCompat("concat"))

python/paddle/fluid/tests/unittests/ir/inference/test_conv_act_mkldnn_fuse_pass.py

@@ -53,8 +53,6 @@ class TestConvActMkldnnFusePass(PassAutoScanTest):
         data_format = prog_config.ops[0].attrs["data_format"]
         filter_shape = prog_config.weights["filter"].shape
         input_shape = prog_config.inputs["input_x"].shape
-        if data_format != "NCHW":
-            return False
         if padding_algorithm == "VALID":
             if ((input_shape[2] - (dilations[0] * (filter_shape[2] - 1) + 1)) / strides[0] + 1) <= 1 or \
             ((input_shape[3] - (dilations[1] * (filter_shape[3] - 1) + 1)) / strides[1] + 1) <= 1:
@@ -80,8 +78,8 @@ class TestConvActMkldnnFusePass(PassAutoScanTest):
         x_shape = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=100), min_size=4, max_size=4))
-        x_shape[1] = draw(st.integers(min_value=1, max_value=10))
+                    min_value=5, max_value=100), min_size=4, max_size=4))
+        x_shape[1] = draw(st.integers(min_value=5, max_value=10))
 
         # 2. Generate legal attr:data_format of conv2d
         data_format = draw(st.sampled_from(["NCHW", "NHWC"]))
@@ -90,7 +88,7 @@ class TestConvActMkldnnFusePass(PassAutoScanTest):
         f_shape = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=7), min_size=4, max_size=4))
+                    min_value=1, max_value=5), min_size=4, max_size=4))
         if data_format == "NCHW":
             f_shape[1] = x_shape[1]
         else:

python/paddle/fluid/tests/unittests/ir/inference/test_conv_bias_mkldnn_fuse_pass.py

@@ -53,8 +53,6 @@ class TestConvBiasMkldnnFusePass(PassAutoScanTest):
         data_format = prog_config.ops[0].attrs["data_format"]
         filter_shape = prog_config.weights["filter"].shape
         input_shape = prog_config.inputs["input_x"].shape
-        if data_format != "NCHW":
-            return False
         if padding_algorithm == "VALID":
             if ((input_shape[2] - (dilations[0] * (filter_shape[2] - 1) + 1)) / strides[0] + 1) <= 1 or \
             ((input_shape[3] - (dilations[1] * (filter_shape[3] - 1) + 1)) / strides[1] + 1) <= 1:
@@ -80,8 +78,8 @@ class TestConvBiasMkldnnFusePass(PassAutoScanTest):
         x_shape = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=100), min_size=4, max_size=4))
-        x_shape[1] = draw(st.integers(min_value=1, max_value=10))
+                    min_value=5, max_value=100), min_size=4, max_size=4))
+        x_shape[1] = draw(st.integers(min_value=5, max_value=10))
 
         # 2. Generate legal attr:data_format of conv2d
         data_format = draw(st.sampled_from(["NCHW", "NHWC"]))
@@ -90,7 +88,7 @@ class TestConvBiasMkldnnFusePass(PassAutoScanTest):
         f_shape = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=7), min_size=4, max_size=4))
+                    min_value=1, max_value=4), min_size=4, max_size=4))
         if data_format == "NCHW":
             f_shape[1] = x_shape[1]
         else:
@@ -100,7 +98,7 @@ class TestConvBiasMkldnnFusePass(PassAutoScanTest):
         strides = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=5), min_size=2, max_size=2))
+                    min_value=1, max_value=4), min_size=2, max_size=2))
 
         # 5. Generate legal attr:padding_algorithm of conv2d
         padding_algorithm = draw(st.sampled_from(["EXPLICIT", "SAME", "VALID"]))
@@ -109,7 +107,7 @@ class TestConvBiasMkldnnFusePass(PassAutoScanTest):
         padding = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=5), min_size=4, max_size=4))
+                    min_value=1, max_value=4), min_size=4, max_size=4))
 
         # 7. Generate legal attr:groups of conv2d
         groups = draw(st.integers(min_value=1, max_value=3))
@@ -118,7 +116,7 @@ class TestConvBiasMkldnnFusePass(PassAutoScanTest):
         dilations = draw(
             st.lists(
                 st.integers(
-                    min_value=1, max_value=5), min_size=2, max_size=2))
+                    min_value=1, max_value=4), min_size=2, max_size=2))
 
         # 9. Generate legal shape of input:bias of elementwise_add
         bias_shape = [f_shape[0]]

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_conv_concat_relu_mkldnn_fuse_pass.py

@@ -27,15 +27,6 @@ import hypothesis.strategies as st
 
 class TestConvConcatReluMkldnnFusePass(PassAutoScanTest):
     def is_program_valid(self, program_config: ProgramConfig) -> bool:
-        attrs = [
-            program_config.ops[i].attrs
-            for i in range(len(program_config.ops))
-        ]
-        # If the problem has been fixed, the judgment 
-        # needs to be deleted!!!
-        if attrs[0]['data_format'] == "NHWC":
-            return False
-
         return True
 
     def sample_program_config(self, draw):

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_conv_gelu_fuse_pass.py

@@ -27,15 +27,6 @@ import hypothesis.strategies as st
 
 class TestConvGeluMkldnnFusePass(PassAutoScanTest):
     def is_program_valid(self, program_config: ProgramConfig) -> bool:
-        attrs = [
-            program_config.ops[i].attrs
-            for i in range(len(program_config.ops))
-        ]
-        # If the problem has been fixed, the judgment 
-        # needs to be deleted!!!
-        if attrs[0]['data_format'] == "NHWC":
-            return False
-
         return True
 
     def sample_program_config(self, draw):
@@ -108,19 +99,6 @@ class TestConvGeluMkldnnFusePass(PassAutoScanTest):
         config = self.create_inference_config(use_mkldnn=True)
         yield config, ["conv2d"], (1e-5, 1e-5)
 
-    # If the problem has been fixed, the judgment 
-    # needs to be deleted!!!
-    def add_ignore_pass_case(self):
-        def teller1(program_config, predictor_config):
-            if program_config.ops[0].attrs['data_format'] == "NHWC":
-                return True
-            return False
-
-        self.add_ignore_check_case(
-            teller1, SkipReasons.PASS_ACCURACY_ERROR,
-            "The output format of conv2d is wrong when data_format attribute is NHWC"
-        )
-
     def test(self):
         self.run_and_statis(quant=False, passes=["conv_gelu_mkldnn_fuse_pass"])
 

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_conv_hard_sigmoid_fuse_pass.py

@@ -27,15 +27,6 @@ import hypothesis.strategies as st
 
 class TestConvHardSigmoidMkldnnFusePass(PassAutoScanTest):
     def is_program_valid(self, program_config: ProgramConfig) -> bool:
-        attrs = [
-            program_config.ops[i].attrs
-            for i in range(len(program_config.ops))
-        ]
-        # If the problem has been fixed, the judgment 
-        # needs to be deleted!!!
-        if attrs[0]['data_format'] == "NHWC":
-            return False
-
         return True
 
     def sample_program_config(self, draw):

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_conv_hard_swish_fuse_pass.py

@@ -27,15 +27,6 @@ import hypothesis.strategies as st
 
 class TestConvHardSwishMkldnnFusePass(PassAutoScanTest):
     def is_program_valid(self, program_config: ProgramConfig) -> bool:
-        attrs = [
-            program_config.ops[i].attrs
-            for i in range(len(program_config.ops))
-        ]
-        # If the problem has been fixed, the judgment 
-        # needs to be deleted!!!
-        if attrs[0]['data_format'] == "NHWC":
-            return False
-
         return True
 
     def sample_program_config(self, draw):

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_conv_transpose_bias_fuse_pass.py

@@ -32,9 +32,9 @@ class TestConvTransposeMkldnnFusePass(PassAutoScanTest):
             for i in range(len(program_config.ops))
         ]
 
-        # If the problem has been fixed, the judgment 
-        # needs to be deleted!!!
-        if attrs[0]['data_format'] == "NHWC":
+        if attrs[0]['data_format'] == "NCHW" and attrs[1]["axis"] == 3:
+            return False
+        if attrs[0]['data_format'] == "NHWC" and attrs[1]["axis"] == 1:
             return False
 
         return True
@@ -46,7 +46,7 @@ class TestConvTransposeMkldnnFusePass(PassAutoScanTest):
         groups = draw(st.sampled_from([1, 2, 4, 8]))
         paddings = draw(st.sampled_from([[0, 3], [1, 2, 3, 4]]))
         strides = draw(st.sampled_from([[1, 1], [2, 2], [1, 2]]))
-        axis = draw(st.sampled_from([1]))
+        axis = draw(st.sampled_from([1, 3]))
         batch_size = draw(st.integers(min_value=1, max_value=4))
 
         def generate_input():
@@ -110,7 +110,9 @@ class TestConvTransposeMkldnnFusePass(PassAutoScanTest):
 
     def test(self):
         self.run_and_statis(
-            quant=False, passes=["conv_transpose_bias_mkldnn_fuse_pass"])
+            quant=False,
+            max_duration=300,
+            passes=["conv_transpose_bias_mkldnn_fuse_pass"])
 
 
 if __name__ == "__main__":