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95 lines
2.8 KiB
95 lines
2.8 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.common.api import ms_function
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from mindspore.ops import operations as P
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x0 = np.array([[True, True], [True, False], [False, False]])
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axis0 = 0
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keep_dims0 = True
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x1 = np.array([[True, True], [True, False], [False, False]])
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axis1 = 0
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keep_dims1 = False
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x2 = np.array([[True, True], [True, False], [False, False]])
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axis2 = 1
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keep_dims2 = True
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x3 = np.array([[True, True], [True, False], [False, False]])
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axis3 = 1
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keep_dims3 = False
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context.set_context(device_target='GPU')
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class ReduceAny(nn.Cell):
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def __init__(self):
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super(ReduceAny, self).__init__()
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self.x0 = Tensor(x0)
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self.axis0 = axis0
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self.keep_dims0 = keep_dims0
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self.x1 = Tensor(x1)
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self.axis1 = axis1
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self.keep_dims1 = keep_dims1
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self.x2 = Tensor(x2)
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self.axis2 = axis2
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self.keep_dims2 = keep_dims2
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self.x3 = Tensor(x3)
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self.axis3 = axis3
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self.keep_dims3 = keep_dims3
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@ms_function
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def construct(self):
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return (P.ReduceAny(self.keep_dims0)(self.x0, self.axis0),
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P.ReduceAny(self.keep_dims1)(self.x1, self.axis1),
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P.ReduceAny(self.keep_dims2)(self.x2, self.axis2),
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P.ReduceAny(self.keep_dims3)(self.x3, self.axis3))
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_ReduceAny():
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reduce_any = ReduceAny()
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output = reduce_any()
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expect0 = np.all(x0, axis=axis0, keepdims=keep_dims0)
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np.allclose(output[0].asnumpy(), expect0)
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assert output[0].shape == expect0.shape
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expect1 = np.all(x1, axis=axis1, keepdims=keep_dims1)
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np.allclose(output[1].asnumpy(), expect1)
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assert output[1].shape == expect1.shape
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expect2 = np.all(x2, axis=axis2, keepdims=keep_dims2)
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np.allclose(output[2].asnumpy(), expect2)
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assert output[2].shape == expect2.shape
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expect3 = np.all(x3, axis=axis3, keepdims=keep_dims3)
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np.allclose(output[3].asnumpy(), expect3)
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assert output[3].shape == expect3.shape
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