# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np import paddle paddle.enable_static() np.random.seed(10) paddle.seed(10) class TestNormalAPI_out_parameter(unittest.TestCase): def test_out_with_shape(self): paddle.disable_static() shape = [2, 3] out_tensor = paddle.empty(shape, dtype='float32') original_ptr = out_tensor.data_ptr() result = paddle.normal(mean=0.0, std=1.0, shape=shape, out=out_tensor) self.assertEqual(result.data_ptr(), original_ptr) self.assertEqual(result.data_ptr(), out_tensor.data_ptr()) self.assertEqual(list(result.shape), shape) paddle.enable_static() def test_out_with_mean_tensor(self): paddle.disable_static() mean_tensor = paddle.to_tensor([1.0, 2.0, 3.0]) shape = [3] out_tensor = paddle.empty(shape, dtype='float32') original_ptr = out_tensor.data_ptr() result = paddle.normal(mean=mean_tensor, std=1.0, out=out_tensor) self.assertEqual(result.data_ptr(), original_ptr) self.assertEqual(result.data_ptr(), out_tensor.data_ptr()) self.assertEqual(list(result.shape), shape) paddle.enable_static() def test_out_with_std_tensor(self): paddle.disable_static() std_tensor = paddle.to_tensor([1.0, 2.0, 3.0]) shape = [3] out_tensor = paddle.empty(shape, dtype='float32') original_ptr = out_tensor.data_ptr() result = paddle.normal(mean=0.0, std=std_tensor, out=out_tensor) self.assertEqual(result.data_ptr(), original_ptr) self.assertEqual(result.data_ptr(), out_tensor.data_ptr()) self.assertEqual(list(result.shape), shape) paddle.enable_static() def test_out_with_mean_std_tensors(self): paddle.disable_static() mean_tensor = paddle.to_tensor([1.0, 2.0, 3.0]) std_tensor = paddle.to_tensor([0.5, 1.0, 1.5]) shape = [3] out_tensor = paddle.empty(shape, dtype='float32') original_ptr = out_tensor.data_ptr() result = paddle.normal(mean=mean_tensor, std=std_tensor, out=out_tensor) self.assertEqual(result.data_ptr(), original_ptr) self.assertEqual(result.data_ptr(), out_tensor.data_ptr()) self.assertEqual(list(result.shape), shape) paddle.enable_static() def test_out_with_complex_mean(self): paddle.disable_static() shape = [2, 3] out_tensor = paddle.empty(shape, dtype='complex64') original_ptr = out_tensor.data_ptr() result = paddle.normal( mean=1.0 + 1.0j, std=1.0, shape=shape, out=out_tensor ) self.assertEqual(result.data_ptr(), original_ptr) self.assertEqual(result.data_ptr(), out_tensor.data_ptr()) self.assertEqual(list(result.shape), shape) self.assertEqual(result.dtype, paddle.complex64) paddle.enable_static() def test_out_with_complex_mean_tensor(self): paddle.disable_static() mean_tensor = paddle.to_tensor([1.0 + 1.0j, 2.0 + 2.0j, 3.0 + 3.0j]) shape = [3] out_tensor = paddle.empty(shape, dtype='complex64') original_ptr = out_tensor.data_ptr() result = paddle.normal(mean=mean_tensor, std=1.0, out=out_tensor) self.assertEqual(result.data_ptr(), original_ptr) self.assertEqual(result.data_ptr(), out_tensor.data_ptr()) self.assertEqual(list(result.shape), shape) self.assertEqual(result.dtype, paddle.complex64) paddle.enable_static() class TestNormalAPI_size_alias(unittest.TestCase): def test_size_alias_basic(self): paddle.disable_static() shape = [2, 3] out = paddle.normal(mean=0.0, std=1.0, size=shape) self.assertEqual(list(out.shape), shape) paddle.enable_static() if __name__ == "__main__": unittest.main()