Metadata-Version: 2.0
Name: tensorpack
Version: 0.1.5
Summary: Neural Network Toolbox on TensorFlow
Home-page: https://github.com/ppwwyyxx/tensorpack
Author: TensorPack contributors
Author-email: ppwwyyxxc@gmail.com
License: Apache
Keywords: tensorflow,deep learning,neural network
Platform: UNKNOWN
Requires-Dist: functools32
Requires-Dist: msgpack-numpy
Requires-Dist: msgpack-python
Requires-Dist: numpy
Requires-Dist: pyzmq
Requires-Dist: six
Requires-Dist: subprocess32
Requires-Dist: termcolor
Requires-Dist: tqdm (>4.11.1)
Provides-Extra: all
Requires-Dist: h5py; extra == 'all'
Requires-Dist: lmdb; extra == 'all'
Requires-Dist: matplotlib; extra == 'all'
Requires-Dist: pillow; extra == 'all'
Requires-Dist: scikit-learn; extra == 'all'
Requires-Dist: scipy; extra == 'all'
Requires-Dist: tornado; extra == 'all'

tensorpack
==========

Neural Network Toolbox on TensorFlow

|Build Status|

Docs & tutorials should be ready within a month. See some
`examples <examples>`__ to learn about the framework:

Vision:
~~~~~~~

-  `DoReFa-Net: train binary / low-bitwidth CNN on
   ImageNet <examples/DoReFa-Net>`__
-  `Train ResNet on ImageNet / Cifar10 / SVHN <examples/ResNet>`__
-  `InceptionV3 on ImageNet <examples/Inception/inceptionv3.py>`__
-  `Fully-convolutional Network for Holistically-Nested Edge
   Detection(HED) <examples/HED>`__
-  `Spatial Transformer Networks on MNIST
   addition <examples/SpatialTransformer>`__
-  `Visualize Saliency Maps by Guided ReLU <examples/Saliency>`__
-  `Similarity Learning on MNIST <examples/SimilarityLearning>`__

Reinforcement Learning:
~~~~~~~~~~~~~~~~~~~~~~~

-  `Deep Q-Network(DQN) variants on Atari
   games <examples/DeepQNetwork>`__
-  `Asynchronous Advantage Actor-Critic(A3C) with demos on OpenAI
   Gym <examples/A3C-Gym>`__

Unsupervised Learning:
~~~~~~~~~~~~~~~~~~~~~~

-  `Generative Adversarial Network(GAN) variants <examples/GAN>`__,
   including DCGAN, InfoGAN, Conditional GAN, Image to Image.

Speech / NLP:
~~~~~~~~~~~~~

-  `LSTM-CTC for speech recognition <examples/CTC-TIMIT>`__
-  `char-rnn for fun <examples/Char-RNN>`__
-  `LSTM language model on PennTreebank <examples/PennTreebank>`__

The examples are not only for demonstration of the framework -- you can
train them and reproduce the results in papers.

Features:
---------

Describe your training task with three components:

1. **Model**, or graph. ``models/`` has some scoped abstraction of
   common models, but you can simply use any symbolic functions
   available in tensorflow, or most functions in
   slim/tflearn/tensorlayer. ``LinearWrap`` and ``argscope`` simplify
   large models (`vgg
   example <https://github.com/ppwwyyxx/tensorpack/blob/master/examples/load-vgg16.py>`__).

2. **DataFlow**. tensorpack allows and encourages complex data
   processing.

   -  All data producer has an unified interface, allowing them to be
      composed to perform complex preprocessing.
   -  Use Python to easily handle any data format, yet still keep good
      performance thanks to multiprocess prefetch & TF Queue prefetch.
      For example, InceptionV3 can run in the same speed as the official
      code which reads data by TF operators.

3. **Callbacks**, including everything you want to do apart from the
   training iterations, such as:

   -  Change hyperparameters during training
   -  Print some tensors of interest
   -  Run inference on a test dataset
   -  Run some operations once a while
   -  Send loss to your phone

With the above components defined, tensorpack trainer will run the
training iterations for you. Multi-GPU training is off-the-shelf by
simply switching the trainer. You can also define your own trainer for
non-standard training (e.g. GAN).

Install:
--------

Dependencies:

-  Python 2 or 3
-  TensorFlow >= 1.0.0rc0
-  Python bindings for OpenCV
-  (optional) use tcmalloc if running with large data

::

    pip install --user -U git+https://github.com/ppwwyyxx/tensorpack.git
    pip install --user -r opt-requirements.txt # (some optional dependencies required by certain submodules, you can install later if prompted)

.. |Build Status| image:: https://travis-ci.org/ppwwyyxx/tensorpack.svg?branch=master
   :target: https://travis-ci.org/ppwwyyxx/tensorpack


