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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.common.tensor import Tensor
- from mindspore.nn import Cell
- from mindspore.ops import operations as P
-
-
- class Net(Cell):
- def __init__(self):
- super(Net, self).__init__()
- self.lessequal = P.LessEqual()
-
- def construct(self, x, y):
- return self.lessequal(x, y)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_lessequal():
- x = Tensor(np.array([[1, 2, 3]]).astype(np.float32))
- y = Tensor(np.array([[2]]).astype(np.float32))
- expect = [[True, True, False]]
- x1 = Tensor(np.array([[1, 2, 3]]).astype(np.int16))
- y1 = Tensor(np.array([[2]]).astype(np.int16))
- expect = [[True, True, False]]
- x2 = Tensor(np.array([[1, 2, 3]]).astype(np.uint8))
- y2 = Tensor(np.array([[2]]).astype(np.uint8))
- expect = [[True, True, False]]
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
- lessequal = Net()
- output = lessequal(x, y)
- assert np.all(output.asnumpy() == expect)
- output = lessequal(x1, y1)
- assert np.all(output.asnumpy() == expect)
- output = lessequal(x2, y2)
- assert np.all(output.asnumpy() == expect)
-
- context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
- lessequal = Net()
- output = lessequal(x, y)
- assert np.all(output.asnumpy() == expect)
- output = lessequal(x1, y1)
- assert np.all(output.asnumpy() == expect)
- output = lessequal(x2, y2)
- assert np.all(output.asnumpy() == expect)
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