add matmul_to_mul matmul_v2_to_mul matmul_v2_to_matmul test case (#37645)

* add matmul_to_mul matmul_v2_to_mul matmul_v2_to_matmul test case

* modify skip func to ignore_pass_case func

* rebuild CI

* rebuild CI

* add test_map_xx_pass timeout

* add test_map_xx_pass timeout

* merge from develop

* add timeout notest;test=coverage

* Cmakelist add timeout

* add timeout

* add attr of matmul_v2

* add trt skip

* delete trt config

* add skip,  mul diff on 3080

python/paddle/fluid/tests/unittests/ir/inference/CMakeLists.txt

@@ -103,6 +103,9 @@ if (WITH_MKLDNN AND TENSORRT_FOUND AND WITH_GPU)
   set_tests_properties(test_flatten2_matmul_fuse_pass PROPERTIES TIMEOUT 240)
   set_tests_properties(test_squeeze2_matmul_fuse_pass PROPERTIES TIMEOUT 240)
   set_tests_properties(test_reshape2_matmul_fuse_pass PROPERTIES TIMEOUT 240)
+  set_tests_properties(test_map_matmul_v2_to_matmul_pass PROPERTIES TIMEOUT 240)
+  set_tests_properties(test_map_matmul_v2_to_mul_pass PROPERTIES TIMEOUT 240)
+  set_tests_properties(test_map_matmul_to_mul_pass PROPERTIES TIMEOUT 240)
 endif()
 
 if (WITH_MKLDNN)

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

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from auto_scan_test import PassAutoScanTest, IgnoreReasons
+from program_config import TensorConfig, ProgramConfig, OpConfig
+import numpy as np
+import paddle.inference as paddle_infer
+from functools import partial
+from typing import Optional, List, Callable, Dict, Any, Set
+import unittest
+
+import hypothesis
+from hypothesis import given, settings, seed, example, assume, reproduce_failure
+import hypothesis.strategies as st
+
+
+class TestMapMatmulToMulPass(PassAutoScanTest):
+    """
+     x_var    y_var(persistable)
+       \       /
+         matmul  
+    """
+
+    def sample_predictor_configs(self, program_config):
+        # cpu
+        config = self.create_inference_config(use_gpu=False)
+        yield config, ["mul", ], (1e-5, 1e-5)
+
+        # for gpu
+        config = self.create_inference_config(use_gpu=True)
+        yield config, ["mul", ], (1e-5, 1e-5)
+
+        # TRT
+        # config = self.create_trt_inference_config()
+        # config.enable_tensorrt_engine(
+        #     max_batch_size=10,
+        #     workspace_size=10240,
+        #     min_subgraph_size=0,
+        #     precision_mode=paddle_infer.PrecisionType.Float32,
+        #     use_static=False,
+        #     use_calib_mode=False)
+        # yield config, ["mul", ], (1e-5, 1e-5)
+
+    def add_ignore_pass_case(self):
+        # Here we put some skip rules to avoid known bugs
+        def teller1(program_config, predictor_config):
+            if predictor_config.use_gpu():
+                # On 3080, the results of MatMul and Mul are different
+                return True
+
+            if predictor_config.tensorrt_engine_enabled():
+                # On 3080, the results of MatMul and Mul are different
+                return True
+
+                x_shape = list(program_config.inputs["matmul_x"].shape)
+                if len(x_shape) > 5:
+                    return True
+            return False
+
+        self.add_ignore_check_case(
+            teller1, IgnoreReasons.PASS_ACCURACY_ERROR,
+            "The pass error on TRT while shape of mul_x > 5.")
+
+    def sample_program_config(self, draw):
+        # 1. Generate shape and attr of matmul
+        x_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=1, max_value=8), min_size=2, max_size=5))
+        y_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=1, max_value=8), min_size=2, max_size=2))
+        y_shape[0] = x_shape[-1]
+        alpha = 1.0
+        transpose_X = False
+        transpose_Y = False
+
+        matmul_op = OpConfig(
+            "matmul",
+            inputs={"X": ["matmul_x"],
+                    "Y": ["matmul_y"]},
+            outputs={"Out": ["matmul_out"]},
+            alpha=alpha,
+            transpose_X=transpose_X,
+            transpose_Y=transpose_Y,
+            fused_reshape_X=[],
+            fused_reshape_Y=[],
+            fused_transpose_X=[],
+            fused_transpose_Y=[],
+            fused_reshape_Out=[],
+            fused_transpose_Out=[], )
+
+        ops = [matmul_op, ]
+        weights = {"matmul_y": TensorConfig(shape=y_shape), }
+        inputs = {"matmul_x": TensorConfig(shape=x_shape), }
+        program_config = ProgramConfig(
+            ops=ops,
+            weights=weights,
+            inputs=inputs,
+            outputs=ops[-1].outputs["Out"], )
+        return program_config
+
+    def test(self):
+        self.run_and_statis(
+            quant=False,
+            max_examples=100,
+            passes=["map_matmul_to_mul_pass"],
+            max_duration=180)
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ir/inference/test_map_matmul_v2_to_matmul_pass.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from auto_scan_test import PassAutoScanTest, IgnoreReasons
+from program_config import TensorConfig, ProgramConfig, OpConfig
+import numpy as np
+import paddle.inference as paddle_infer
+from functools import partial
+from typing import Optional, List, Callable, Dict, Any, Set
+import unittest
+
+import hypothesis
+from hypothesis import given, settings, seed, example, assume, reproduce_failure
+import hypothesis.strategies as st
+
+
+class TestMapMatmulToMulPass(PassAutoScanTest):
+    """
+     x_var    y_var(persistable)
+       \       /
+        matmul_v2  
+    """
+
+    def sample_predictor_configs(self, program_config):
+        # cpu
+        config = self.create_inference_config(use_gpu=False)
+        yield config, ["matmul", ], (1e-5, 1e-5)
+
+        # for gpu
+        config = self.create_inference_config(use_gpu=True)
+        yield config, ["matmul", ], (1e-5, 1e-5)
+
+        # TRT
+        # config = self.create_trt_inference_config()
+        # config.enable_tensorrt_engine(
+        #     max_batch_size=10,
+        #     workspace_size=10240,
+        #     min_subgraph_size=0,
+        #     precision_mode=paddle_infer.PrecisionType.Float32,
+        #     use_static=False,
+        #     use_calib_mode=False)
+        # yield config, ["matmul", ], (1e-5, 1e-5)
+
+    def add_ignore_pass_case(self):
+        # Here we put some skip rules to avoid known bugs
+        def teller1(program_config, predictor_config):
+            if predictor_config.tensorrt_engine_enabled():
+                # On 3080, the results of MatMul and Mul are different
+                return True
+
+                x_shape = list(program_config.inputs["matmul_x"].shape)
+                if len(x_shape) > 5:
+                    return True
+            return False
+
+        self.add_ignore_check_case(
+            teller1, IgnoreReasons.PASS_ACCURACY_ERROR,
+            "The pass error on TRT while shape of mul_x > 5.")
+
+    def sample_program_config(self, draw):
+        # 1. Generate shape and attr of matmul
+        x_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=1, max_value=8), min_size=2, max_size=5))
+        y_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=1, max_value=8), min_size=2, max_size=2))
+        transpose_X = draw(st.booleans())
+        transpose_Y = draw(st.booleans())
+        if transpose_X:
+            if transpose_Y:
+                y_shape[1] = x_shape[-2]
+            else:
+                y_shape[0] = x_shape[-2]
+        else:
+            if transpose_Y:
+                y_shape[1] = x_shape[-1]
+            else:
+                y_shape[0] = x_shape[-1]
+
+        y_shape = x_shape[0:len(x_shape) - 2] + y_shape
+        alpha = 1.0
+
+        matmul_op = OpConfig(
+            "matmul_v2",
+            inputs={"X": ["matmul_x"],
+                    "Y": ["matmul_y"]},
+            outputs={"Out": ["matmul_out"]},
+            alpha=alpha,
+            trans_x=transpose_X,
+            trans_y=transpose_Y,
+            fused_reshape_Out=[],
+            fused_transpose_Out=[],
+            fused_reshape_X=[],
+            fused_reshape_Y=[],
+            fused_transpose_X=[],
+            fused_transpose_Y=[], )
+
+        ops = [matmul_op, ]
+        weights = {}
+        inputs = {
+            "matmul_x": TensorConfig(shape=x_shape),
+            "matmul_y": TensorConfig(shape=y_shape),
+        }
+
+        program_config = ProgramConfig(
+            ops=ops,
+            weights=weights,
+            inputs=inputs,
+            outputs=ops[-1].outputs["Out"], )
+        return program_config
+
+    def test(self):
+        self.run_and_statis(
+            quant=False,
+            max_examples=100,
+            passes=["map_matmul_v2_to_matmul_pass"])
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ir/inference/test_map_matmul_v2_to_mul_pass.py

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from auto_scan_test import PassAutoScanTest, IgnoreReasons
+from program_config import TensorConfig, ProgramConfig, OpConfig
+import numpy as np
+import paddle.inference as paddle_infer
+from functools import partial
+from typing import Optional, List, Callable, Dict, Any, Set
+import unittest
+
+import hypothesis
+from hypothesis import given, settings, seed, example, assume, reproduce_failure
+import hypothesis.strategies as st
+
+
+class TestMapMatmulToMulPass(PassAutoScanTest):
+    """
+     x_var    y_var(persistable)
+       \       /
+       matmul_v2  
+    """
+
+    def sample_predictor_configs(self, program_config):
+        # cpu
+        config = self.create_inference_config(use_gpu=False)
+        yield config, ["mul", ], (1e-5, 1e-5)
+
+        # for gpu
+        config = self.create_inference_config(use_gpu=True)
+        yield config, ["mul", ], (1e-5, 1e-5)
+
+        # TRT
+        # config = self.create_trt_inference_config()
+        # config.enable_tensorrt_engine(
+        #     max_batch_size=10,
+        #     workspace_size=10240,
+        #     min_subgraph_size=0,
+        #     precision_mode=paddle_infer.PrecisionType.Float32,
+        #     use_static=False,
+        #     use_calib_mode=False)
+        # yield config, ["mul", ], (1e-5, 1e-5)
+
+    def add_ignore_pass_case(self):
+        # Here we put some skip rules to avoid known bugs
+        def teller1(program_config, predictor_config):
+            if predictor_config.tensorrt_engine_enabled():
+                # On 3080, the results of MatMul and Mul are different
+                return True
+
+                x_shape = list(program_config.inputs["matmul_x"].shape)
+                if len(x_shape) > 5:
+                    return True
+            return False
+
+        self.add_ignore_check_case(
+            teller1, IgnoreReasons.PASS_ACCURACY_ERROR,
+            "The pass error on TRT while shape of mul_x > 5.")
+
+    def sample_program_config(self, draw):
+        # 1. Generate shape and attr of matmul
+        x_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=1, max_value=8), min_size=2, max_size=5))
+        y_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=1, max_value=8), min_size=2, max_size=2))
+        y_shape[0] = x_shape[-1]
+        alpha = 1.0
+        transpose_X = False
+        transpose_Y = False
+
+        matmul_op = OpConfig(
+            "matmul_v2",
+            inputs={"X": ["matmul_x"],
+                    "Y": ["matmul_y"]},
+            outputs={"Out": ["matmul_out"]},
+            alpha=alpha,
+            trans_x=transpose_X,
+            trans_y=transpose_Y,
+            fused_reshape_Out=[],
+            fused_transpose_Out=[],
+            fused_reshape_X=[],
+            fused_reshape_Y=[],
+            fused_transpose_X=[],
+            fused_transpose_Y=[], )
+
+        ops = [matmul_op, ]
+        weights = {"matmul_y": TensorConfig(shape=y_shape), }
+        inputs = {"matmul_x": TensorConfig(shape=x_shape), }
+        program_config = ProgramConfig(
+            ops=ops,
+            weights=weights,
+            inputs=inputs,
+            outputs=ops[-1].outputs["Out"], )
+        return program_config
+
+    def test(self):
+        self.run_and_statis(
+            quant=False, max_examples=100,
+            passes=["map_matmul_v2_to_mul_pass"])
+
+
+if __name__ == "__main__":
+    unittest.main()