Metadata-Version: 1.0
Name: PreTrainingChain
Version: 0.1.4
Summary: Scalable, configurable and Pre-training DNN using chainer
Home-page: https://github.com/fukatani/PreTrainingChain
Author: Ryosuke Fukatani
Author-email: nannyakannya@gmail.com
License: Apache License 2.0
Description: Introduction

        ============

        

        Extension of chainer. ChainList for the purpose of network

        scalability/congirablity/Pre-training executablity for deep leaning.

        (You need to get deep learning framework "chainer" from

        http://chainer.org/)

        

        feature:

        ========

        

        1) You can define network structure by list or tuple such as [784, 250, 200, 160, 10].

        --------------------------------------------------------------------------------------

        

        This feature accelerate your deep network development. If you call this

        class by ChainClassfier([784, 250, 200, 160, 10]), you can generate

        ChainList-> (F.Linear(784, 250), F.Linear(250, 200), F.Linear(200, 160),

        F.Linear(160, 10)) You can change network structure without any hard

        coding.

        

        2) Pre-training executable.

        ---------------------------

        

        You can execute pre-training only by calling

        AbstractChain.pre\_training(train\_data). Pretraining is executed by

        using Bengio method. (http://arxiv.org/pdf/1206.5538.pdf) If length of

        train\_Data is zero, Pre-training is skipped.

        

        3)Usage as scikit-learn library, and correpond to GridSearch parameter tuning.

        ------------------------------------------------------------------------------

        

        You can use PreTraining\_chain as scikit-learn library, So

        ChainClassfier.fit, ChainClassfier.predict, ChainClassfier.score is

        usable. Also you can use sklearn.gridsearchCV. Please see

        `GridSearchExample.py. <https://github.com/fukatani/PreTrainingChain/blob/master/PreTrainingChain/GridSearchExample.py>`__

        

        Software Requirements

        =====================

        

        -  Python (2.7)

        -  chainer >= 1.8.0

        -  scikit-learn

        

        Installation

        ============

        

        ::

        

            $ pip install PreTrainingChain

        

        or

        

        ::

        

            $ git clone https://github.com/fukatani/PreTrainingChain.git

        

        Example

        =======

        

        Implement example is here

        https://github.com/fukatani/PreTrainingChain/blob/master/PreTrainingChain/Example.py

        You have to override add\_last\_layer method and loss\_function method.

        

        Example.py is implement for mnist classification.

        

        ::

        

            $ python Example.py

        

            fetch MNIST dataset

            Successed data fetching

            Pre-training test loss: 0.0895392745733

            Pre-training test loss: 0.000182752759429

            Pre-training test loss: 5.92054857407e-05

            Pre-training test loss: 1.82532239705e-05

            test_loss: 2.30244994164

            test_accuracy: 0.0799999982119

            test_loss: 2.30086517334

            test_accuracy: 0.189999997616

            test_loss: 2.28533029556

            test_accuracy: 0.27500000596

            test_loss: 2.25788879395

            test_accuracy: 0.294999986887

            test_loss: 2.21044063568

            test_accuracy: 0.284999996424

            test_loss: 2.13255786896

            test_accuracy: 0.280000001192

            test_loss: 2.09592270851

            test_accuracy: 0.305000007153

            test_loss: 2.05419230461

            test_accuracy: 0.294999986887

            test_loss: 2.04007315636

            test_accuracy: 0.294999986887

            test_loss: 2.01762104034

            test_accuracy: 0.289999991655

        

        License

        =======

        

        Apache License 2.0 (http://www.apache.org/licenses/LICENSE-2.0)

        

        Copyright

        =========

        

        Copyright (C) 2015, Ryosuke Fukatani

        

        Related Project and Site

        ========================

        

        chainer http://docs.chainer.org/en/stable/index.html

        

        Blog entry(Japanese)

        http://segafreder.hatenablog.com/entry/2015/12/30/183319

        
Keywords: chainer,newral network,machine leaning
Platform: UNKNOWN
