wehub-resource-sync
60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
# 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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import unittest
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import numpy as np
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import paddle
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class DotOpEmptyInput(unittest.TestCase):
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def test_1d_input(self):
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data = np.array([], dtype=np.float32)
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x = paddle.to_tensor(np.reshape(data, [0]), dtype='float32')
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y = paddle.to_tensor(np.reshape(data, [0]), dtype='float32')
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np_out = np.dot(data, data)
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pd_out = paddle.dot(x, y)
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self.assertEqual(np_out, pd_out)
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def test_2d_input(self):
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data = np.array([], dtype=np.float32)
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x = paddle.to_tensor(np.reshape(data, [0, 0]), dtype='float32')
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y = paddle.to_tensor(np.reshape(data, [0, 0]), dtype='float32')
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pd_out = paddle.dot(x, y)
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self.assertEqual(
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pd_out.shape,
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[
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0,
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],
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)
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def test_3d_input_error(self):
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data = np.array([], dtype=np.float32)
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x = paddle.to_tensor(np.reshape(data, [0, 0, 0]), dtype='float32')
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y = paddle.to_tensor(np.reshape(data, [0, 0, 0]), dtype='float32')
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self.assertRaisesRegex(
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RuntimeError,
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r"ShapeError: The dimensions of input tensor X \(\[0, 0, 0\]\) should be 1 or 2",
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paddle.dot,
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x,
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y,
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)
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if __name__ == '__main__':
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unittest.main()
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