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data
data
 
 
dataset
dataset
 
 
net
net
 
 
pure_checkpoints
pure_checkpoints
 
 
tools
tools
 
 
.gitignore
.gitignore
 
 
README.md
README.md
 
 
check_flaten.ipynb
check_flaten.ipynb
 
 
config.py
config.py
 
 
pure_net.ipynb
pure_net.ipynb
 
 
test_net.py
test_net.py
 
 
test_pure_net.py
test_pure_net.py
 
 
train_origin_net.py
train_origin_net.py
 
 
train_pure_net.py
train_pure_net.py
 
 

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剪枝步骤

  1. 运行 train_origin_net.py 生成原始的模型，并保存其参数
  2. 运行 pure_net.ipynb 对每一层进行剪枝操作，并保存下剪枝后的维度和权重， 保存为 pb 文件
  3. 运行 test_origin_net.py 和 test_pure_net.py 查看剪枝后的模型与原模型精度对比
  4. 运行 train_pure_net.py rebirth剪枝后的模型

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