PocketFlow ChannelPrunedLearner代码详解

下面代码不包括DDPG强化学习参数优化器和Distill蒸馏训练

PocketFlow框架安装

conda create --name PocketFlow python=3.6

source activate PocketFlow

pip install tensorflow-gpu=1.10.0

pip install numpy=1.14.5

conda install panda

conda install scikit-learn

cifar10数据集准备

cifar-10：使用binary版本

wget https://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz

下载完成后，解压到data目录

并在path.conf中设置路径：data_dir_local_cifar10 = /home/mars/hewu/tensorflow/PocketFlow/data/cifar-10-batches-bin

执行代码

./scripts/run_local.sh nets/resnet_at_cifar10_run.py 

官方教程需要在工程根目录配置path.conf文件，然后执行上述脚本。个人觉得不太方便调试，直接启动py，单步跟踪，更加便于理解程序逻辑。

nets/resnet_at_cifar10_run.py --model_http_url https://api.ai.tencent.com/pocketflow --data_dir_local /home/mars/hewu/tensorflow/PocketFlow/data/cifar-10-batches-bin --learner channel --cp_prune_option uniform

程序入口-main.py

#/home/mars/hewu/tensorflow/PocketFlow/main.py
from nets.resnet_at_cifar10 import ModelHelper
from learners.learner_utils import create_learner

#1创建模型helper和learner
model_helper = ModelHelper()#网络和数据集的类
learner = create_learner(sw_writer,model_helper)#跳转到不同的压缩算法learner

#2进入训练，或者评估
learner.train()
learner.evaluate()

通道裁剪学习器-channel_pruning/learner.py

#/home/mars/hewu/tensorflow/PocketFlow/learners/channel_pruning/learner.py
from learners.distillation_helper import DistillationHelper #蒸馏相关
from learners.abstract_learner import AbstractLearner
from learners.channel_pruning.model_wrapper import Model #模型相关
from learners.channel_pruning.channel_pruner import ChannelPruner #裁剪相关
from rl_agents.ddpg.agent import Agent as DdpgAgent #强化学习代理DDPG

#继承自AbstractLearner
class ChannelPrunedLearner(AbstractLearner):
  #继承初始化