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65 lines
2.2 KiB
65 lines
2.2 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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from mindspore.common.tensor import Tensor
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from mindspore.nn import Cell
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from mindspore.ops import operations as P
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class Net(Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.lessequal = P.LessEqual()
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def construct(self, x, y):
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return self.lessequal(x, y)
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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_lessequal():
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x = Tensor(np.array([[1, 2, 3]]).astype(np.float32))
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y = Tensor(np.array([[2]]).astype(np.float32))
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expect = [[True, True, False]]
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x1 = Tensor(np.array([[1, 2, 3]]).astype(np.int16))
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y1 = Tensor(np.array([[2]]).astype(np.int16))
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expect = [[True, True, False]]
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x2 = Tensor(np.array([[1, 2, 3]]).astype(np.uint8))
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y2 = Tensor(np.array([[2]]).astype(np.uint8))
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expect = [[True, True, False]]
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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lessequal = Net()
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output = lessequal(x, y)
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assert np.all(output.asnumpy() == expect)
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output = lessequal(x1, y1)
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assert np.all(output.asnumpy() == expect)
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output = lessequal(x2, y2)
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assert np.all(output.asnumpy() == expect)
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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lessequal = Net()
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output = lessequal(x, y)
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assert np.all(output.asnumpy() == expect)
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output = lessequal(x1, y1)
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assert np.all(output.asnumpy() == expect)
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output = lessequal(x2, y2)
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assert np.all(output.asnumpy() == expect)
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