1# Copyright 2023 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 16from mindspore.communication import init, get_rank 17import mindspore as ms 18import mindspore.nn as nn 19import mindspore.ops as ops 20from mindspore import context 21 22 23context.set_context(mode=ms.GRAPH_MODE) 24context.set_context(jit_level="O2") 25init() 26 27 28class Net(nn.Cell): 29 def __init__(self): 30 super(Net, self).__init__() 31 self.all_reduce_sum = ops.AllReduce(ops.ReduceOp.SUM) 32 33 def construct(self, x): 34 return self.all_reduce_sum(x) 35 36value = get_rank() 37input_x = ms.Tensor(np.array([[value]]).astype(np.float32)) 38net = Net() 39output = net(input_x) 40