Merge pull request #5 from alexqdh/master

add readme

AutoDL Design/README.md

+# AutoDL Design 简介
+
+## 目录
+- [安装](#安装)
+- [简介](#简介)
+- [数据准备](#数据准备)
+- [模型训练](#模型训练)
+
+## 安装
+在当前目录下运行样例代码需要PadddlePaddle Fluid的v.1.3.0或以上的版本。如果你的运行环境中的PaddlePaddle低于此版本，请根据安装文档中的说明来更新PaddlePaddle。
+* 安装Python2.7
+* 训练执行依赖[PARL](https://github.com/PaddlePaddle/PARL) 框架和[absl-py](https://github.com/abseil/abseil-py/tree/master/absl) 库，通过如下命令安装
+```
+	pip install parl
+	pip install absl-py
+```
+
+
+## 简介
+[AutoDL](http://www.paddlepaddle.org/paddle/ModelAutoDL)是一种高效的自动搜索构建最佳网络结构的方法，通过增强学习在不断训练过程中得到定制化高质量的模型。系统由两部分组成，第一部分是网络结构的编码器，第二部分是网络结构的评测器。编码器通常以 RNN 的方式把网络结构进行编码，然后评测器把编码的结果拿去进行训练和评测，拿到包括准确率、模型大小在内的一些指标，反馈给编码器，编码器进行修改，再次编码，如此迭代。经过若干次迭代以后，最终得到一个设计好的模型。这里开源的AutoDl Design是基于PaddlePaddle框架的一种AutoDL技术实现。第二节介绍AutoDL Design的使用步骤。第三节介绍AutoDL Design的实现原理与示例。
+
+## 数据准备
+* 克隆[PaddlePaddle/AutoDL](https://github.com/PaddlePaddle/AutoDL.git)到测试机，并进入AutoDL Design路径。 
+* 下载[CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz)训练数据，并放入AutoDL Design/cifar路径下并解压，按如下命令执行`dataset_maker.py` 生成10类每类100张图片的pickle训练小数据集。
+```
+tar zxf cifar-10-python.tar.gz
+python dataset_maker.py
+```
+
+## 模型训练
+AutoDL Design在训练过程中每次通过Agent的策略网络生成用于训练的Tokens和邻接矩阵Adj，然后Trainer通过Tokens和Adj进行CNN训练网络的组建与训练，训练20个epoch以后返回训练的acc值作为Reward返回给Agent，Agent收到Reward值以后更新策略，通过不断的迭代，最终可以自动搜索到效果不错的深度神经网络。
+![图片](./img/cnn_net.png)
+这里提供了如下两种测试的方法。
+
+### 针对生成tokens个数的收敛性测试
+由于CNN训练每次执行时间长，为了测试整体Agent框架的正确性，这里我们把生成tokens个数作为模拟CNN训练的返回Reward，最终自动搜索出来的网络可以使得tokens的个数越来越多。这里tokens向量总长度设置的是20。执行以下命令：
+```
+	export FLAGS_fraction_of_gpu_memory_to_use=0.98
+	export FLAGS_eager_delete_tensor_gb=0.0
+	export FLAGS_fast_eager_deletion_mode=1
+	CUDA_VISIBLE_DEVICES=0 python -u simple_main.py
+```
+预期结果：
+日志中 `average rewards`逐步向20收敛递增
+
+```
+Simple run target is 20
+mid=0, average rewards=2.500
+...
+mid=450, average rewards=17.100
+mid=460, average rewards=17.000
+
+```
+
+### AutoDL网络自动搜索训练
+基于CIFAR-10小数据集上执行自动网络搜索策略，每次先执行Agent策略网络生成新的策略，然后Trainer根据生成的策略去进行模型的训练与Reward(即acc指标)结果的反馈，最终不断迭代搜索到准确率更高的模型网络结构。执行以下命令：
+```
+	export FLAGS_fraction_of_gpu_memory_to_use=0.98
+	export FLAGS_eager_delete_tensor_gb=0.0
+	export FLAGS_fast_eager_deletion_mode=1
+	CUDA_VISIBLE_DEVICES=0 python -u main.py
+```
+__注意:__ 这里训练需要使用两张卡来训练，Agent使用的卡为`CUDA_VISIBLE_DEVICES=0`(设置在启动`main.py`命令中)；Trainer训练使用卡为`CUDA_VISIBLE_DEVICES=1`(设置在[autodl.py](https://github.com/PaddlePaddle/AutoDL/blob/master/AutoDL%20Design/autodl.py#L124)文件中)
+
+预期结果：
+日志中 `average accuracy`逐步增大
+
+```
+step = 0, average accuracy = 0.633
+step = 1, average accuracy = 0.688
+step = 2, average accuracy = 0.626
+step = 3, average accuracy = 0.682
+......
+step = 842, average accuracy = 0.823
+step = 843, average accuracy = 0.825
+step = 844, average accuracy = 0.808
+......
+```
+### 结果展示
+
+![图片](./img/search_result.png)
+横坐标是迭代的step轮数，纵坐标是模型训练的acc指标，通过图中所示，通过不断的迭代搜索，使得自动构建模型的效果在不断增强。

AutoDL Design/autodl.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/autodl_agent.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/cifar/dataset_maker.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/distribute_generator.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/models/inception.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/models/layers.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/models/ops.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/nn.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/preprocess.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/reader.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rig hts Reserved
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/train.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/inception_train/utils.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/main.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/policy_model.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/reinforce_policy_gradient.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/simple_main.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

AutoDL Design/utils.py

 #!/usr/bin/env python
-# -*- encoding:utf-8 -*-
+# -*- coding:utf-8 -*-
 # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");