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81 lines
2.9 KiB
81 lines
2.9 KiB
# Copyright (c) 2018 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 paddle
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import paddle.fluid as fluid
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from paddle import ones_like
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from paddle.fluid import core, Program, program_guard
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class TestOnesLikeAPIError(unittest.TestCase):
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def test_errors(self):
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with program_guard(Program(), Program()):
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x = paddle.data('x', [3, 4])
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self.assertRaises(TypeError, ones_like, x, 'int8')
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class TestOnesLikeAPI(unittest.TestCase):
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def test_api(self):
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shape = [3, 4]
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startup_program = Program()
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train_program = Program()
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with program_guard(train_program, startup_program):
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x = paddle.data('X', shape)
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# 'bool', 'float32', 'float64', 'int32', 'int64'
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out1 = ones_like(x)
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out2 = ones_like(x, np.bool)
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out3 = ones_like(x, 'float64')
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out4 = ones_like(x, 'int32')
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out5 = ones_like(x, 'int64')
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place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
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) else fluid.CPUPlace()
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exe = fluid.Executor(place)
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outs = exe.run(train_program,
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feed={'X': np.ones(shape).astype('float32')},
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fetch_list=[out1, out2, out3, out4, out5])
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for i, dtype in enumerate(
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[np.float32, np.bool, np.float64, np.int32, np.int64]):
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self.assertEqual(outs[i].dtype, dtype)
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self.assertEqual((outs[i] == np.ones(shape, dtype)).all(), True)
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class TestOnesLikeImpeartive(unittest.TestCase):
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def test_out(self):
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shape = [3, 4]
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place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
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) else fluid.CPUPlace()
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with paddle.imperative.guard(place):
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x = paddle.imperative.to_variable(np.ones(shape))
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for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]:
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out = ones_like(x, dtype)
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self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(),
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True)
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out = paddle.tensor.ones_like(x)
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self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True)
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out = paddle.tensor.creation.ones_like(x)
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self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True)
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if __name__ == "__main__":
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unittest.main()
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