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- # Copyright 2020 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 NetElu(nn.Cell):
- def __init__(self):
- super(NetElu, self).__init__()
- self.elu = P.Elu()
-
- def construct(self, x):
- return self.elu(x)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_elu_fp16():
- x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]).astype(np.float16))
- expect = np.array([[-0.632, 4.0, -0.999], [2.0, -0.993, 9.0]]).astype(np.float16)
- error = np.ones(shape=[2, 3]) * 1.0e-6
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
- elu = NetElu()
- output = elu(x)
- diff = output.asnumpy() - expect
- assert np.all(diff < error)
-
- context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
- elu = NetElu()
- output = elu(x)
- diff = output.asnumpy() - expect
- assert np.all(diff < error)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_elu_fp32():
- x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]).astype(np.float32))
- expect = np.array([[-0.632, 4.0, -0.999], [2.0, -0.993, 9.0]]).astype(np.float32)
- error = np.ones(shape=[2, 3]) * 1.0e-6
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
- elu = NetElu()
- output = elu(x)
- diff = output.asnumpy() - expect
- assert np.all(diff < error)
-
- context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
- elu = NetElu()
- output = elu(x)
- diff = output.asnumpy() - expect
- assert np.all(diff < error)
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