chore: import upstream snapshot with attribution
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# Copyright (c) 2021 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 os
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import unittest
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import numpy as np
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from utils import check_output, extra_cc_args, extra_nvcc_args, paddle_includes
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import paddle
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from paddle.utils.cpp_extension import get_build_directory, load
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from paddle.utils.cpp_extension.extension_utils import run_cmd
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# Because Windows don't use docker, the shared lib already exists in the
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# cache dir, it will not be compiled again unless the shared lib is removed.
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file = f'{get_build_directory()}\\custom_simple_slice\\custom_simple_slice.pyd'
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if os.name == 'nt' and os.path.isfile(file):
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cmd = f'del {file}'
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run_cmd(cmd, True)
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custom_ops = load(
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name='custom_simple_slice_jit',
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sources=['custom_simple_slice_op.cc'],
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extra_include_paths=paddle_includes, # add for Coverage CI
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extra_cxx_cflags=extra_cc_args, # test for cc flags
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extra_cuda_cflags=extra_nvcc_args, # test for nvcc flags
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verbose=True,
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)
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class TestCustomSimpleSliceJit(unittest.TestCase):
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def test_slice_output(self):
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np_x = np.random.random((5, 2)).astype("float32")
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x = paddle.to_tensor(np_x)
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custom_op_out = custom_ops.custom_simple_slice(x, 2, 3)
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np_out = np_x[2:3]
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check_output(custom_op_out, np_out, "out")
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if __name__ == "__main__":
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unittest.main()
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