Metadata-Version: 1.0
Name: PreTrainingChain
Version: 0.1.3
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
