1# Copyright 2020 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 as ms 18from mindspore import context, Tensor, Parameter 19from mindspore.common.api import _cell_graph_executor 20from mindspore.nn import Cell, TrainOneStepCell, Momentum 21from mindspore.ops import operations as P 22 23 24class Net(Cell): 25 def __init__(self, mul_weight, strategy1=None, strategy2=None): 26 super().__init__() 27 self.mul = P.Mul().shard(strategy1) 28 self.sigmoid = P.Sigmoid().shard(strategy2) 29 self.mul_weight = Parameter(mul_weight, "w1") 30 31 def construct(self, x, b): 32 out = self.mul(x, self.mul_weight) 33 out = self.sigmoid(out) 34 return out 35 36 37_x = Tensor(np.ones([64, 32]), dtype=ms.float32) 38_w1 = Tensor(np.ones([64, 32]), dtype=ms.float32) 39_b = Tensor(np.ones([64, 32]), dtype=ms.float32) 40 41 42def compile_net(net): 43 optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9) 44 train_net = TrainOneStepCell(net, optimizer) 45 train_net.set_auto_parallel() 46 train_net.set_train() 47 _cell_graph_executor.compile(train_net, _x, _b) 48 context.reset_auto_parallel_context() 49 50 51def test_auto_parallel_activation(): 52 context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=16, global_rank=0) 53 strategy1 = ((4, 4), (4, 4)) 54 strategy2 = None 55 net = Net(_w1, strategy1, strategy2) 56 compile_net(net) 57