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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
- from mindspore import Tensor
- import mindspore.ops.operations._grad_ops as P
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_acosgrad_fp32():
- error = np.ones(4) * 1.0e-7
- x_np = np.array([0, -0.25, 0.5, 0.3]).astype(np.float32)
- dout_np = np.array([1, 1, 1, 1]).astype(np.float32)
- output_ms = P.ACosGrad()(Tensor(x_np), Tensor(dout_np))
- expect = np.array([-1, -1.0327955, -1.1547005, -1.0482849])
- diff = output_ms.asnumpy() - expect
- assert np.all(diff < error)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_acosgrad_fp16():
- error = np.ones(4) * 1.0e-3
- x_np = np.array([0, -0.25, 0.5, 0.3]).astype(np.float16)
- dout_np = np.array([1, 1, 1, 1]).astype(np.float16)
- output_ms = P.ACosGrad()(Tensor(x_np), Tensor(dout_np))
- expect = np.array([-1, -1.033, -1.154, -1.048])
- diff = output_ms.asnumpy() - expect
- assert np.all(diff < error)
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