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- # Copyright 2020-2021 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
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
- def cos(nptype):
- np.random.seed(0)
- x_np = np.random.rand(2, 3, 4, 4).astype(nptype)
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
- output_ms = P.Cos()(Tensor(x_np))
- output_np = np.cos(x_np)
- assert np.allclose(output_ms.asnumpy(), output_np)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_cos_float16():
- cos(np.float16)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_cos_float32():
- cos(np.float32)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_cos_float64():
- cos(np.float64)
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