wehub-resource-sync
144 lines
4.4 KiB
Python
144 lines
4.4 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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paddle.enable_static()
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np.random.seed(10)
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paddle.seed(10)
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class TestNormalAPI_out_parameter(unittest.TestCase):
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def test_out_with_shape(self):
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paddle.disable_static()
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shape = [2, 3]
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out_tensor = paddle.empty(shape, dtype='float32')
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original_ptr = out_tensor.data_ptr()
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result = paddle.normal(mean=0.0, std=1.0, shape=shape, out=out_tensor)
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self.assertEqual(result.data_ptr(), original_ptr)
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self.assertEqual(result.data_ptr(), out_tensor.data_ptr())
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self.assertEqual(list(result.shape), shape)
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paddle.enable_static()
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def test_out_with_mean_tensor(self):
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paddle.disable_static()
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mean_tensor = paddle.to_tensor([1.0, 2.0, 3.0])
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shape = [3]
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out_tensor = paddle.empty(shape, dtype='float32')
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original_ptr = out_tensor.data_ptr()
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result = paddle.normal(mean=mean_tensor, std=1.0, out=out_tensor)
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self.assertEqual(result.data_ptr(), original_ptr)
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self.assertEqual(result.data_ptr(), out_tensor.data_ptr())
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self.assertEqual(list(result.shape), shape)
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paddle.enable_static()
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def test_out_with_std_tensor(self):
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paddle.disable_static()
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std_tensor = paddle.to_tensor([1.0, 2.0, 3.0])
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shape = [3]
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out_tensor = paddle.empty(shape, dtype='float32')
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original_ptr = out_tensor.data_ptr()
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result = paddle.normal(mean=0.0, std=std_tensor, out=out_tensor)
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self.assertEqual(result.data_ptr(), original_ptr)
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self.assertEqual(result.data_ptr(), out_tensor.data_ptr())
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self.assertEqual(list(result.shape), shape)
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paddle.enable_static()
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def test_out_with_mean_std_tensors(self):
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paddle.disable_static()
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mean_tensor = paddle.to_tensor([1.0, 2.0, 3.0])
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std_tensor = paddle.to_tensor([0.5, 1.0, 1.5])
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shape = [3]
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out_tensor = paddle.empty(shape, dtype='float32')
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original_ptr = out_tensor.data_ptr()
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result = paddle.normal(mean=mean_tensor, std=std_tensor, out=out_tensor)
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self.assertEqual(result.data_ptr(), original_ptr)
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self.assertEqual(result.data_ptr(), out_tensor.data_ptr())
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self.assertEqual(list(result.shape), shape)
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paddle.enable_static()
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def test_out_with_complex_mean(self):
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paddle.disable_static()
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shape = [2, 3]
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out_tensor = paddle.empty(shape, dtype='complex64')
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original_ptr = out_tensor.data_ptr()
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result = paddle.normal(
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mean=1.0 + 1.0j, std=1.0, shape=shape, out=out_tensor
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)
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self.assertEqual(result.data_ptr(), original_ptr)
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self.assertEqual(result.data_ptr(), out_tensor.data_ptr())
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self.assertEqual(list(result.shape), shape)
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self.assertEqual(result.dtype, paddle.complex64)
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paddle.enable_static()
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def test_out_with_complex_mean_tensor(self):
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paddle.disable_static()
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mean_tensor = paddle.to_tensor([1.0 + 1.0j, 2.0 + 2.0j, 3.0 + 3.0j])
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shape = [3]
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out_tensor = paddle.empty(shape, dtype='complex64')
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original_ptr = out_tensor.data_ptr()
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result = paddle.normal(mean=mean_tensor, std=1.0, out=out_tensor)
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self.assertEqual(result.data_ptr(), original_ptr)
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self.assertEqual(result.data_ptr(), out_tensor.data_ptr())
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self.assertEqual(list(result.shape), shape)
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self.assertEqual(result.dtype, paddle.complex64)
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paddle.enable_static()
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class TestNormalAPI_size_alias(unittest.TestCase):
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def test_size_alias_basic(self):
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paddle.disable_static()
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shape = [2, 3]
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out = paddle.normal(mean=0.0, std=1.0, size=shape)
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self.assertEqual(list(out.shape), shape)
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paddle.enable_static()
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if __name__ == "__main__":
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unittest.main()
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