Metadata-Version: 2.0
Name: tensorpack
Version: 0.6.1
Summary: Neural Network Toolbox on TensorFlow
Home-page: https://github.com/ppwwyyxx/tensorpack
Author: TensorPack contributors
Author-email: ppwwyyxxc@gmail.com
License: Apache
Description-Content-Type: UNKNOWN
Keywords: tensorflow,deep learning,neural network
Platform: UNKNOWN
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Provides-Extra: all
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tensorpack
==========

A neural net training interface based on TensorFlow.

|Build Status| |ReadTheDoc| |Gitter chat|

See some `examples <examples>`__ to learn about the framework.
Everything runs on multiple GPUs, because why not?

Vision:
~~~~~~~

-  `Train ResNet/SE-ResNet on ImageNet <examples/ResNet>`__
-  `Train Faster-RCNN on COCO object detection <examples/FasterRCNN>`__
-  `Generative Adversarial Network(GAN) variants <examples/GAN>`__,
   including DCGAN, InfoGAN, Conditional GAN, WGAN, BEGAN, DiscoGAN,
   Image to Image, CycleGAN.
-  `DoReFa-Net: train binary / low-bitwidth CNN on
   ImageNet <examples/DoReFa-Net>`__
-  `Fully-convolutional Network for Holistically-Nested Edge
   Detection(HED) <examples/HED>`__
-  `Spatial Transformer Networks on MNIST
   addition <examples/SpatialTransformer>`__
-  `Visualize CNN saliency maps <examples/Saliency>`__
-  `Similarity learning on MNIST <examples/SimilarityLearning>`__

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

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

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

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

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

Features:
---------

It's Yet Another TF wrapper, but different in: 1. It's not a model
wrapper. + There are already too many symbolic function wrappers.
Tensorpack includes only a few common models, but you can use any other
model wrappers within tensorpack, such as
sonnet/Keras/slim/tflearn/tensorlayer/....

2. Focus on **training speed**.

   -  Speed comes for free with tensorpack -- it uses TensorFlow in the
      **correct way**. On various CNNs, it runs 1.5~1.7x faster than the
      equivalent Keras code.

   -  Data-parallel multi-GPU/distributed training is off-the-shelf to
      use. It is as fast as Google's `official
      benchmark <https://www.tensorflow.org/performance/benchmarks>`__.

   -  See
      `tensorpack/benchmarks <https://github.com/tensorpack/benchmarks>`__
      for some benchmark scripts.

3. Focus on **large datasets**.

   -  It's painful to read/preprocess data through TF. tensorpack helps
      you load large datasets (e.g. ImageNet) in **pure Python** with
      autoparallelization. It also naturally works with TF Queues or
      tf.data.

4. Interface of extensible **Callbacks**. Write a callback to implement
   everything you want to do apart from the training iterations, and
   enable it with one line of code. Common examples include:

   -  Change hyperparameters during training
   -  Print some tensors of interest
   -  Monitor GPU utilization
   -  Send error rate to your phone

See
`tutorials <http://tensorpack.readthedocs.io/en/latest/tutorial/index.html>`__
to know more about these features.

Install:
--------

Dependencies:

-  Python 2 or 3
-  TensorFlow >= 1.0.0 (>=1.1.0 for Multi-GPU)
-  Python bindings for OpenCV (Optional, but required by a lot of
   features)

   ::

       pip install -U git+https://github.com/ppwwyyxx/tensorpack.git
       # or add `--user` to avoid system-wide installation.

   If you only want to use ``tensorpack.dataflow`` alone as a data
   processing library, TensorFlow is also optional.

.. |Build Status| image:: https://travis-ci.org/ppwwyyxx/tensorpack.svg?branch=master
   :target: https://travis-ci.org/ppwwyyxx/tensorpack
.. |ReadTheDoc| image:: https://readthedocs.org/projects/tensorpack/badge/?version=latest
   :target: http://tensorpack.readthedocs.io/en/latest/index.html
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