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125 lines
4.0 KiB
125 lines
4.0 KiB
# 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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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle.fluid as fluid
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import paddle
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def np_masked_select(x, mask):
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result = np.empty(shape=(0), dtype=x.dtype)
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for ele, ma in zip(np.nditer(x), np.nditer(mask)):
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if ma:
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result = np.append(result, ele)
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return result.flatten()
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class TestMaskedSelectOp(OpTest):
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def setUp(self):
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self.init()
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self.op_type = "masked_select"
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x = np.random.random(self.shape).astype("float64")
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mask = np.array(np.random.randint(2, size=self.shape, dtype=bool))
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out = np_masked_select(x, mask)
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self.inputs = {'X': x, 'Mask': mask}
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self.outputs = {'Y': out}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(['X'], 'Y')
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def init(self):
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self.shape = (50, 3)
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class TestMaskedSelectOp1(TestMaskedSelectOp):
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def init(self):
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self.shape = (6, 8, 9, 18)
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class TestMaskedSelectOp2(TestMaskedSelectOp):
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def init(self):
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self.shape = (168, )
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class TestMaskedSelectAPI(unittest.TestCase):
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def test_imperative_mode(self):
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paddle.disable_static()
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shape = (88, 6, 8)
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np_x = np.random.random(shape).astype('float32')
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np_mask = np.array(np.random.randint(2, size=shape, dtype=bool))
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x = paddle.to_tensor(np_x)
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mask = paddle.to_tensor(np_mask)
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out = paddle.masked_select(x, mask)
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np_out = np_masked_select(np_x, np_mask)
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self.assertEqual(np.allclose(out.numpy(), np_out), True)
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paddle.enable_static()
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def test_static_mode(self):
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shape = [8, 9, 6]
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x = paddle.fluid.data(shape=shape, dtype='float32', name='x')
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mask = paddle.fluid.data(shape=shape, dtype='bool', name='mask')
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np_x = np.random.random(shape).astype('float32')
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np_mask = np.array(np.random.randint(2, size=shape, dtype=bool))
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out = paddle.masked_select(x, mask)
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np_out = np_masked_select(np_x, np_mask)
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exe = paddle.static.Executor(place=paddle.CPUPlace())
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res = exe.run(paddle.static.default_main_program(),
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feed={"x": np_x,
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"mask": np_mask},
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fetch_list=[out])
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self.assertEqual(np.allclose(res, np_out), True)
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class TestMaskedSelectError(unittest.TestCase):
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def test_error(self):
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with paddle.static.program_guard(paddle.static.Program(),
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paddle.static.Program()):
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shape = [8, 9, 6]
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x = paddle.fluid.data(shape=shape, dtype='float32', name='x')
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mask = paddle.fluid.data(shape=shape, dtype='bool', name='mask')
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mask_float = paddle.fluid.data(
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shape=shape, dtype='float32', name='mask_float')
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np_x = np.random.random(shape).astype('float32')
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np_mask = np.array(np.random.randint(2, size=shape, dtype=bool))
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def test_x_type():
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paddle.masked_select(np_x, mask)
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self.assertRaises(TypeError, test_x_type)
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def test_mask_type():
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paddle.masked_select(x, np_mask)
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self.assertRaises(TypeError, test_mask_type)
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def test_mask_dtype():
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paddle.masked_select(x, mask_float)
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self.assertRaises(TypeError, test_mask_dtype)
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if __name__ == '__main__':
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unittest.main()
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