# 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)