# 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 import mindspore.nn as nn from mindspore import Tensor from mindspore.ops import operations as P class NetArgmaxWithValue(nn.Cell): def __init__(self): super(NetArgmaxWithValue, self).__init__() axis1 = 0 axis2 = -1 self.argmax1 = P.ArgMaxWithValue(axis1) self.argmax2 = P.ArgMaxWithValue(axis2) self.argmax3 = P.ArgMaxWithValue() def construct(self, x): return (self.argmax1(x), self.argmax2(x), self.argmax3(x)) @pytest.mark.level0 @pytest.mark.platform_x86_gpu_training @pytest.mark.env_onecard def test_argmaxwithvalue(): x = Tensor(np.array([[1., 20., 5.], [67., 8., 9.], [130., 24., 15.], [0.3, -0.4, -15.]]).astype(np.float32)) expect1 = np.array([2, 2, 2]).astype(np.float32) expect2 = np.array([1, 0, 0, 0]).astype(np.float32) expect11 = np.array([130, 24, 15]).astype(np.float32) expect22 = np.array([20, 67, 130, 0.3]).astype(np.float32) context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU") argmax = NetArgmaxWithValue() output = argmax(x) assert (output[0][0].asnumpy() == expect1).all() assert (output[0][1].asnumpy() == expect11).all() assert (output[1][0].asnumpy() == expect2).all() assert (output[1][1].asnumpy() == expect22).all() assert (output[2][0].asnumpy() == expect1).all() assert (output[2][1].asnumpy() == expect11).all() context.set_context(mode=context.GRAPH_MODE, device_target="GPU") argmax = NetArgmaxWithValue() output = argmax(x) assert (output[0][0].asnumpy() == expect1).all() assert (output[0][1].asnumpy() == expect11).all() assert (output[1][0].asnumpy() == expect2).all() assert (output[1][1].asnumpy() == expect22).all() assert (output[2][0].asnumpy() == expect1).all() assert (output[2][1].asnumpy() == expect11).all()