Add compatibility check for four mkldnn pass (#27364)
* Add pass compatibility check for four mkldnn pass, test=developrevert-27520-disable_pr
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5 years ago
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from inference_pass_test import InferencePassTest
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.core import AnalysisConfig
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from paddle.fluid.core import PassVersionChecker
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class ConvActivationMkldnnFusePassTest(InferencePassTest):
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def setUp(self):
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self.set_params()
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with fluid.program_guard(self.main_program, self.startup_program):
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data = fluid.data(
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name="data", shape=[-1, 3, 100, 100], dtype="float32")
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conv_out = fluid.layers.conv2d(
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data,
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num_filters=self.conv_num_filters,
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filter_size=self.conv_filter_size,
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bias_attr=self.conv_bias_attr,
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act=self.act)
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self.feeds = {
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"data": np.random.random((1, 3, 100, 100)).astype("float32")
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}
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self.fetch_list = [conv_out]
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self.enable_mkldnn = True
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def set_params(self):
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self.conv_num_filters = 3
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self.conv_filter_size = 3
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self.conv_bias_attr = False
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self.act = "relu"
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self.pass_name = 'conv_relu_mkldnn_fuse_pass'
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def test_check_output(self):
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use_gpu = False
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self.check_output_with_option(use_gpu)
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def test_pass_compatible(self):
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self.assertTrue(PassVersionChecker.IsCompatible(self.pass_name))
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class ConvActivationMkldnnFusePassTest_1(ConvActivationMkldnnFusePassTest):
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def set_params(self):
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self.conv_num_filters = 5
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self.conv_filter_size = 5
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self.conv_bias_attr = True
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self.act = "relu"
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self.pass_name = 'conv_relu_mkldnn_fuse_pass'
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class ConvActivationMkldnnFusePassTest_2(ConvActivationMkldnnFusePassTest):
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def set_params(self):
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self.conv_num_filters = 3
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self.conv_filter_size = 3
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self.conv_bias_attr = False
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self.act = "leaky_relu"
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self.pass_name = 'conv_leaky_relu_mkldnn_fuse_pass'
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class ConvActivationMkldnnFusePassTest_3(ConvActivationMkldnnFusePassTest):
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def set_params(self):
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self.conv_num_filters = 5
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self.conv_filter_size = 5
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self.conv_bias_attr = True
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self.act = "leaky_relu"
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self.pass_name = 'conv_leaky_relu_mkldnn_fuse_pass'
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class ConvActivationMkldnnFusePassTest_4(ConvActivationMkldnnFusePassTest):
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def set_params(self):
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self.conv_num_filters = 3
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self.conv_filter_size = 3
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self.conv_bias_attr = False
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self.act = "relu6"
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self.pass_name = 'conv_relu6_mkldnn_fuse_pass'
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class ConvActivationMkldnnFusePassTest_4(ConvActivationMkldnnFusePassTest):
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def set_params(self):
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self.conv_num_filters = 5
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self.conv_filter_size = 5
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self.conv_bias_attr = True
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self.act = "swish"
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self.pass_name = 'conv_swish_mkldnn_fuse_pass'
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if __name__ == "__main__":
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unittest.main()
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from inference_pass_test import InferencePassTest
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.core import AnalysisConfig
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from paddle.fluid.core import PassVersionChecker
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class ConvConcatReluMkldnnFusePassTest_0(InferencePassTest):
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def setUp(self):
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self.set_params()
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with fluid.program_guard(self.main_program, self.startup_program):
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data_1 = fluid.data(
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name="data_1", shape=[-1, 3, 100, 100], dtype="float32")
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data_2 = fluid.data(
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name="data_2", shape=[-1, 3, 100, 100], dtype="float32")
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conv_1 = fluid.layers.conv2d(
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data_1,
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num_filters=self.conv1_num_filters,
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filter_size=self.conv1_filter_size,
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padding=self.conv1_padding,
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bias_attr=self.conv1_bias_attr)
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conv_2 = fluid.layers.conv2d(
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data_2,
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num_filters=self.conv2_num_filters,
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filter_size=self.conv2_filter_size,
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padding=self.conv2_padding,
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bias_attr=self.conv2_bias_attr)
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concat = fluid.layers.concat(
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[conv_1, conv_2], axis=self.concat_axis)
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out = fluid.layers.relu(concat)
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self.feeds = {
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"data_1": np.random.random((1, 3, 100, 100)).astype("float32"),
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"data_2": np.random.random((1, 3, 100, 100)).astype("float32")
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}
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self.fetch_list = [out]
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self.enable_mkldnn = True
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def set_params(self):
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self.conv1_num_filters = 3
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self.conv1_filter_size = 3
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self.conv1_padding = 0
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self.conv1_bias_attr = False
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self.conv2_num_filters = 3
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self.conv2_filter_size = 3
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self.conv2_padding = 0
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self.conv2_bias_attr = False
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self.concat_axis = 0
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self.pass_name = "conv_concat_relu_mkldnn_fuse_pass"
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def test_check_output(self):
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use_gpu = False
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self.check_output_with_option(use_gpu)
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def test_pass_compatible(self):
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self.assertTrue(PassVersionChecker.IsCompatible(self.pass_name))
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class ConvConcatReluMkldnnFusePassTest_1(ConvConcatReluMkldnnFusePassTest_0):
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def set_params(self):
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self.conv1_num_filters = 3
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self.conv1_filter_size = 3
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self.conv1_padding = 0
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self.conv1_bias_attr = False
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self.conv2_num_filters = 5
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self.conv2_filter_size = 5
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self.conv2_padding = 1
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self.conv2_bias_attr = True
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self.concat_axis = 1
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self.pass_name = "conv_concat_relu_mkldnn_fuse_pass"
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if __name__ == "__main__":
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unittest.main()
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from inference_pass_test import InferencePassTest
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.core import AnalysisConfig
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from paddle.fluid.core import PassVersionChecker
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class MatmulTransposeReshapeMkldnnFusePassTest(InferencePassTest):
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def setUp(self):
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self.set_params()
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with fluid.program_guard(self.main_program, self.startup_program):
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data = fluid.data(
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name="data", shape=self.data_shape, dtype="float32")
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weight = fluid.layers.create_parameter(
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shape=self.weight_shape, dtype="float32")
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matmul = fluid.layers.matmul(
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data,
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weight,
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transpose_x=self.transpose_x,
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transpose_y=self.transpose_y)
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transpose = fluid.layers.transpose(matmul, self.tranpose_perm)
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reshape = fluid.layers.reshape(transpose, shape=self.reshape_shape)
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self.fetch_list = [reshape]
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self.enable_mkldnn = True
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def set_params(self):
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self.data_shape = [-1, 3, 100, 110]
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self.weight_shape = [1, 3, 110, 100]
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self.feeds = {
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"data": np.random.random((1, 3, 100, 110)).astype("float32")
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}
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self.transpose_x = False
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self.transpose_y = False
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self.tranpose_perm = [0, 2, 1, 3]
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self.reshape_shape = [3, 100, 100]
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self.pass_name = 'matmul_transpose_reshape_fuse_pass'
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def test_check_output(self):
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use_gpu = False
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self.check_output_with_option(use_gpu)
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def test_pass_compatible(self):
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self.assertTrue(PassVersionChecker.IsCompatible(self.pass_name))
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class MatmulTransposeReshapeMkldnnFusePassTest_1(
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MatmulTransposeReshapeMkldnnFusePassTest):
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def set_params(self):
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self.data_shape = [-1, 3, 100, 100]
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self.weight_shape = [1, 3, 100, 100]
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self.feeds = {
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"data": np.random.random((1, 3, 100, 100)).astype("float32")
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}
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self.transpose_x = True
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self.transpose_y = True
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self.tranpose_perm = [0, 2, 1, 3]
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self.reshape_shape = [6, 50, 100]
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self.pass_name = 'matmul_transpose_reshape_fuse_pass'
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if __name__ == "__main__":
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unittest.main()
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