1# Copyright 2019 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15import numpy as np 16 17import mindspore.context as context 18import mindspore.nn as nn 19from mindspore import Tensor 20from mindspore.common.api import ms_function 21from mindspore.ops.operations import _grad_ops as G 22 23context.set_context(device_target="Ascend") 24 25 26class Net(nn.Cell): 27 def __init__(self): 28 super(Net, self).__init__() 29 self.bias_add_grad = G.BiasAddGrad() 30 # self.dout = Parameter(initializer( 31 # 'normal', [2, 3, 3, 4]), name='dout') 32 33 @ms_function 34 def construct(self, dout_): 35 return self.bias_add_grad(dout_) 36 37 38dout = np.ones([2, 3, 4, 4]).astype(np.float32) 39bias_add_grad = Net() 40output = bias_add_grad(Tensor(dout)) 41expect_output = np.array([32., 32., 32.]).astype(np.float32) 42assert np.all(output.asnumpy() == expect_output), "bias_add_grad execute failed, please check current code commit" 43print(output.asnumpy()) 44