59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""LeNet."""
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import mindspore.nn as nn
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class LeNet5(nn.Cell):
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"""
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Lenet network
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Args:
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num_class (int): Num classes. Default: 10.
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Returns:
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Tensor, output tensor
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Examples:
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>>> LeNet(num_class=10)
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"""
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def __init__(self, num_class=10, channel=1):
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super(LeNet5, self).__init__()
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self.type = "fusion"
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self.num_class = num_class
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# change `nn.Conv2d` to `nn.Conv2dBnAct`
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self.conv1 = nn.Conv2dBnAct(channel, 6, 5, pad_mode='valid', activation='relu')
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self.conv2 = nn.Conv2dBnAct(6, 16, 5, pad_mode='valid', activation='relu')
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# change `nn.Dense` to `nn.DenseBnAct`
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self.fc1 = nn.DenseBnAct(16 * 5 * 5, 120, activation='relu')
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self.fc2 = nn.DenseBnAct(120, 84, activation='relu')
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self.fc3 = nn.DenseBnAct(84, self.num_class)
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self.max_pool2d = nn.MaxPool2d(kernel_size=2, stride=2)
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self.flatten = nn.Flatten()
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def construct(self, x):
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x = self.conv1(x)
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x = self.max_pool2d(x)
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x = self.conv2(x)
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x = self.max_pool2d(x)
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x = self.flatten(x)
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x = self.fc1(x)
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x = self.fc2(x)
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x = self.fc3(x)
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return x
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