# Copyright (c) 2018 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 from paddle.fluid.tests.unittests.eager_op_test import OpTest from paddle.fluid.tests.unittests.test_gaussian_random_op import ( TestGaussianRandomOp, ) class TestMKLDNNGaussianRandomOpSeed10(TestGaussianRandomOp): def init_kernel_type(self): self.use_mkldnn = True class TestMKLDNNGaussianRandomOpSeed0(TestGaussianRandomOp): def setUp(self): TestGaussianRandomOp.setUp(self) self.use_mkldnn = True self.attrs = { "shape": [123, 92], "mean": 1.0, "std": 2.0, "seed": 10, "use_mkldnn": self.use_mkldnn, } class TestGaussianRandomOp_ZeroDim(OpTest): def setUp(self): self.op_type = "gaussian_random" self.__class__.op_type = "gaussian_random" self.python_api = paddle.normal self.set_attrs() self.inputs = {} self.use_mkldnn = True self.attrs = { "shape": [], "mean": self.mean, "std": self.std, "seed": 10, "use_mkldnn": self.use_mkldnn, } paddle.seed(10) self.outputs = {'Out': np.random.normal(self.mean, self.std, ())} def set_attrs(self): self.mean = 1.0 self.std = 2.0 # TODO(qun) find a way to check a random scalar def test_check_output(self): pass def test_check_grad(self): pass if __name__ == '__main__': unittest.main()