forked from mindspore-Ecosystem/mindspore
69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
# Copyright 2021 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.ops import operations as P
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class ReduceMin(nn.Cell):
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def __init__(self, keep_dims):
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super(ReduceMin, self).__init__()
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self.reduce_min = P.ReduceMin(keep_dims)
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def construct(self, x, axis):
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return self.reduce_min(x, axis)
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def get_output(x, axis, keep_dims, enable_graph_kernel=False):
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context.set_context(enable_graph_kernel=enable_graph_kernel)
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net = ReduceMin(keep_dims)
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output = net(x, axis)
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return output
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def test_reduce_min():
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x0 = Tensor(np.random.normal(0, 1, [2, 3, 4, 4]).astype(np.float32))
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axis0 = 3
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keep_dims0 = True
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expect = get_output(x0, axis0, keep_dims0, False)
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output = get_output(x0, axis0, keep_dims0, True)
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assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
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x1 = Tensor(np.random.normal(0, 1, [2, 3, 4, 4]).astype(np.float32))
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axis1 = 3
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keep_dims1 = False
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expect = get_output(x1, axis1, keep_dims1, False)
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output = get_output(x1, axis1, keep_dims1, True)
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assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
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x2 = Tensor(np.random.normal(0, 1, [2, 3, 1, 4]).astype(np.float32))
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axis2 = 2
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keep_dims2 = True
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expect = get_output(x2, axis2, keep_dims2, False)
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output = get_output(x2, axis2, keep_dims2, True)
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assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
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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_reduce_min_gpu():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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test_reduce_min()
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