# Copyright 2019 Huawei Technologies Co., Ltd # # 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 numpy as np import pytest import mindspore.context as context import mindspore.nn as nn from mindspore import Tensor from mindspore.ops import operations as P class NetLog(nn.Cell): def __init__(self): super(NetLog, self).__init__() self.log = P.Log() def construct(self, x): return self.log(x) @pytest.mark.level0 @pytest.mark.platform_x86_gpu_training @pytest.mark.env_onecard def test_log(): x0_np = np.random.uniform(1, 2, (2, 3, 4, 4)).astype(np.float32) x1_np = np.random.uniform(1, 2, 1).astype(np.float32) x0 = Tensor(x0_np) x1 = Tensor(x1_np) expect0 = np.log(x0_np) expect1 = np.log(x1_np) error0 = np.ones(shape=expect0.shape) * 1.0e-5 error1 = np.ones(shape=expect1.shape) * 1.0e-5 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU") log = NetLog() output0 = log(x0) output1 = log(x1) diff0 = output0.asnumpy() - expect0 assert np.all(diff0 < error0) assert output0.shape == expect0.shape diff1 = output1.asnumpy() - expect1 assert np.all(diff1 < error1) assert output1.shape == expect1.shape context.set_context(mode=context.GRAPH_MODE, device_target="GPU") log = NetLog() output0 = log(x0) output1 = log(x1) diff0 = output0.asnumpy() - expect0 assert np.all(diff0 < error0) assert output0.shape == expect0.shape diff1 = output1.asnumpy() - expect1 assert np.all(diff1 < error1) assert output1.shape == expect1.shape