wehub-resource-sync
65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
# Copyright (c) 2022 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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import unittest
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import hypothesis.strategies as st
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from auto_scan_test import PassAutoScanTest
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from program_config import OpConfig, ProgramConfig, TensorConfig
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import paddle.inference as paddle_infer
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class TestDeleteCIdentityPass(PassAutoScanTest):
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def sample_predictor_configs(self, program_config):
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config = self.create_trt_inference_config()
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config.enable_tensorrt_engine(
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max_batch_size=8,
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workspace_size=0,
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min_subgraph_size=0,
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precision_mode=paddle_infer.PrecisionType.Float32,
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use_static=False,
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use_calib_mode=False,
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)
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yield config, ['relu'], (1e-5, 1e-5)
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def sample_program_config(self, draw):
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n = draw(st.integers(min_value=1, max_value=2))
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relu_op = OpConfig(
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"relu", inputs={"X": ["relu_x"]}, outputs={"Out": ["relu_out"]}
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)
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c_identity_op = OpConfig(
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"c_identity",
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inputs={"X": ["relu_out"]},
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outputs={"Out": ["id_out"]},
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)
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program_config = ProgramConfig(
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ops=[relu_op, c_identity_op],
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weights={},
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inputs={"relu_x": TensorConfig(shape=[n])},
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outputs=["id_out"],
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)
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return program_config
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def test(self):
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self.run_and_statistics(
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max_examples=2,
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min_success_num=2,
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passes=["identity_op_clean_pass"],
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)
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if __name__ == "__main__":
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unittest.main()
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