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- # 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 NetExp(nn.Cell):
- def __init__(self):
- super(NetExp, self).__init__()
- self.exp = P.Exp()
-
- def construct(self, x):
- return self.exp(x)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_exp():
- x0_np = np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.float32)
- x1_np = np.random.uniform(-2, 2, 1).astype(np.float32)
- x0 = Tensor(x0_np)
- x1 = Tensor(x1_np)
- expect0 = np.exp(x0_np)
- expect1 = np.exp(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.GRAPH_MODE, device_target="GPU")
- exp = NetExp()
- output0 = exp(x0)
- diff0 = output0.asnumpy() - expect0
- assert np.all(diff0 < error0)
- assert output0.shape == expect0.shape
- output1 = exp(x1)
- diff1 = output1.asnumpy() - expect1
- assert np.all(diff1 < error1)
- assert output1.shape == expect1.shape
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
- exp = NetExp()
- output0 = exp(x0)
- diff0 = output0.asnumpy() - expect0
- assert np.all(diff0 < error0)
- assert output0.shape == expect0.shape
- output1 = exp(x1)
- diff1 = output1.asnumpy() - expect1
- assert np.all(diff1 < error1)
- assert output1.shape == expect1.shape
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