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# ============================================================================ 15"""LeNet.""" 16import mindspore.nn as nn 17 18 19class LeNet5(nn.Cell): 20 """ 21 Lenet network 22 23 Args: 24 num_class (int): Num classes. Default: 10. 25 26 Returns: 27 Tensor, output tensor 28 Examples: 29 >>> LeNet(num_class=10) 30 31 """ 32 33 def __init__(self, num_class=10, channel=1): 34 super(LeNet5, self).__init__() 35 self.type = "fusion" 36 self.num_class = num_class 37 38 # change `nn.Conv2d` to `nn.Conv2dBnAct` 39 self.conv1 = nn.Conv2dBnAct(channel, 6, 5, pad_mode='valid', activation='relu') 40 self.conv2 = nn.Conv2dBnAct(6, 16, 5, pad_mode='valid', activation='relu') 41 # change `nn.Dense` to `nn.DenseBnAct` 42 self.fc1 = nn.DenseBnAct(16 * 5 * 5, 120, activation='relu') 43 self.fc2 = nn.DenseBnAct(120, 84, activation='relu') 44 self.fc3 = nn.DenseBnAct(84, self.num_class) 45 46 self.max_pool2d = nn.MaxPool2d(kernel_size=2, stride=2) 47 self.flatten = nn.Flatten() 48 49 def construct(self, x): 50 x = self.conv1(x) 51 x = self.max_pool2d(x) 52 x = self.conv2(x) 53 x = self.max_pool2d(x) 54 x = self.flatten(x) 55 x = self.fc1(x) 56 x = self.fc2(x) 57 x = self.fc3(x) 58 return x 59