wehub-resource-sync
86 lines
2.7 KiB
Python
86 lines
2.7 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 os
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import sys
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import unittest
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import numpy as np
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# use dot <CPU, ANY, INT8> as test case.
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class TestCustomKernelDot(unittest.TestCase):
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def setUp(self):
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# compile so and set to current path
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cur_dir = os.path.dirname(os.path.abspath(__file__))
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# --inplace to place output so file to current dir
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cmd = f'cd {cur_dir} && {sys.executable} custom_kernel_dot_setup.py build_ext --inplace'
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os.system(cmd)
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def test_custom_kernel_dot_run(self):
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# test dot run
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x_data = np.random.uniform(1, 5, [2, 10]).astype(np.int8)
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y_data = np.random.uniform(1, 5, [2, 10]).astype(np.int8)
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result = np.sum(x_data * y_data, axis=1).reshape([2, 1])
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import paddle
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paddle.set_device('cpu')
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x = paddle.to_tensor(x_data)
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y = paddle.to_tensor(y_data)
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out = paddle.dot(x, y)
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np.testing.assert_array_equal(
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out.numpy(),
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result,
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err_msg=f'custom kernel dot out: {out.numpy()},\n numpy dot out: {result}',
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)
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class TestCustomKernelDotC(unittest.TestCase):
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def setUp(self):
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# compile so and set to current path
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cur_dir = os.path.dirname(os.path.abspath(__file__))
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# --inplace to place output so file to current dir
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cmd = f'cd {cur_dir} && {sys.executable} custom_kernel_dot_c_setup.py build_ext --inplace'
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os.system(cmd)
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def test_custom_kernel_dot_run(self):
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# test dot run
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x_data = np.random.uniform(1, 5, [2, 10]).astype(np.int8)
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y_data = np.random.uniform(1, 5, [2, 10]).astype(np.int8)
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result = np.sum(x_data * y_data, axis=1).reshape([2, 1])
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import paddle
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paddle.set_device('cpu')
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x = paddle.to_tensor(x_data)
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y = paddle.to_tensor(y_data)
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out = paddle.dot(x, y)
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np.testing.assert_array_equal(
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out.numpy(),
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result,
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err_msg=f'custom kernel dot out: {out.numpy()},\n numpy dot out: {result}',
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)
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if __name__ == '__main__':
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if os.name == 'nt' or sys.platform.startswith('darwin'):
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# only support Linux now
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sys.exit()
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unittest.main()
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