55 lines
2.0 KiB
55 lines
2.0 KiB
# Copyright (c) 2019 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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from __future__ import print_function
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import unittest
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import numpy as np
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import sys
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import paddle.fluid.core as core
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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from paddle.fluid.executor import Executor
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class TestMaskedSelect(unittest.TestCase):
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def test_masked_select(self):
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mask_shape = [4, 1]
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shape = [4, 4]
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data = np.random.random(mask_shape).astype("float32")
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input_data = np.random.random(shape).astype("float32")
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mask_data = data > 0.5
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mask_data_b = np.broadcast_to(mask_data, shape)
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npresult = input_data[np.where(mask_data_b)]
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input_var = layers.create_tensor(dtype="float32", name="input")
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mask_var = layers.create_tensor(dtype="bool", name="mask")
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output = layers.masked_select(input=input_var, mask=mask_var)
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for use_cuda in ([False, True]
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if core.is_compiled_with_cuda() else [False]):
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place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
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exe = Executor(place)
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result = exe.run(fluid.default_main_program(),
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feed={"input": input_data,
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"mask": mask_data},
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fetch_list=[output])
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self.assertTrue(np.isclose(npresult, result).all())
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if __name__ == "__main__":
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unittest.main()
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