wehub-resource-sync
86 lines
3.1 KiB
Python
86 lines
3.1 KiB
Python
# Copyright (c) 2025 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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from paddle import base
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class TestCompatUniqueAPI(unittest.TestCase):
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def test_basic(self):
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paddle.disable_static()
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x = paddle.to_tensor([2, 3, 3, 1, 5, 3])
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result = paddle.compat.unique(x)
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expected = paddle.to_tensor([1, 2, 3, 5], dtype='int64')
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np.testing.assert_allclose(result.numpy(), expected.numpy())
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_, inverse_indices, counts = paddle.compat.unique(
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x, return_inverse=True, return_counts=True
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)
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expected_indices = paddle.to_tensor([1, 2, 2, 0, 3, 2], dtype='int64')
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expected_counts = paddle.to_tensor([1, 1, 3, 1], dtype='int64')
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np.testing.assert_allclose(
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inverse_indices.numpy(), expected_indices.numpy()
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)
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np.testing.assert_allclose(counts.numpy(), expected_counts.numpy())
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x = paddle.to_tensor([[2, 1, 3], [3, 0, 1], [2, 1, 3]])
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result = paddle.compat.unique(x)
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expected = paddle.to_tensor([0, 1, 2, 3], dtype='int64')
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np.testing.assert_allclose(result.numpy(), expected.numpy())
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paddle.enable_static()
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def test_static(self):
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paddle.enable_static()
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with paddle.static.program_guard(
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paddle.static.Program(), paddle.static.Program()
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):
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x = paddle.static.data(name='input', shape=[6], dtype='int64')
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out, inverse_indices, counts = paddle.compat.unique(
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x, return_inverse=True, return_counts=True
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)
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exe = base.Executor(base.CPUPlace())
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x_data = np.array([2, 3, 3, 1, 5, 3], dtype='int64')
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result = exe.run(
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feed={'input': x_data},
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fetch_list=[out, inverse_indices, counts],
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)
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np.testing.assert_allclose(result[1], [1, 2, 2, 0, 3, 2])
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np.testing.assert_allclose(result[2], [1, 1, 3, 1])
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with paddle.static.program_guard(
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paddle.static.Program(), paddle.static.Program()
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):
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x = paddle.static.data(name='input', shape=[3, 3], dtype='int64')
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out = paddle.compat.unique(x)
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exe = base.Executor(base.CPUPlace())
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x_data = np.array([[2, 1, 3], [3, 0, 1], [2, 1, 3]], dtype='int64')
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result = exe.run(feed={'input': x_data}, fetch_list=[out])
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expected = np.array([0, 1, 2, 3], dtype='int64')
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np.testing.assert_allclose(result[0], expected)
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paddle.disable_static()
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if __name__ == '__main__':
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unittest.main()
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