Welcome to TensorLayer

TensorLayer is a Deep Learning (DL) and Reinforcement Learning (RL) library extended from Google TensorFlow. It provides popular DL and RL modules that can be easily customized and assembled for tackling real-world machine learning problems.

Note

If you got problem to read the docs online, you could download the repository on GitHub, then go to /docs/_build/html/index.html to read the docs offline. The _build folder can be generated in docs using make html.

User Guide

The TensorLayer user guide explains how to install TensorFlow, CUDA and cuDNN, how to build and train neural networks using TensorLayer, and how to contribute to the library as a developer.

• Installation
  • Step 1 : Install dependencies
  • Step 2 : TensorFlow
  • Step 3 : TensorLayer
  • Step 4 : GPU support
• Tutorial
  • Before we start
  • TensorLayer is simple
  • Run the MNIST example
  • Understand the MNIST example
  • Run the Pong Game example
  • Understand Reinforcement learning
  • Run the Word2Vec example
  • Understand Word Embedding
  • Run the PTB example
  • Understand LSTM
  • Run the Translation example
  • Understand Translation
  • More info
• Example
  • Basics
  • Computer Vision
  • Natural Language Processing
  • Reinforcement Learning
  • Applications
  • Special Examples
• Development
  • What to contribute
  • How to contribute
• More
  • FQA
  • Recruitment

API Reference

If you are looking for information on a specific function, class or method, this part of the documentation is for you.

• API - Layers
  • Understand layer
  • Your layer
  • Layer list
  • Name Scope and Sharing Parameters
  • Basic layer
  • Input layer
  • Word Embedding Input layer
  • Dense layer
  • Noise layer
  • Convolutional layer (Pro)
  • Convolutional layer (Simplified)
  • Pooling layer
  • Normalization layer
  • Recurrent layer
  • Shape layer
  • Lambda layer
  • Merge layer
  • Connect TF-Slim
  • Parametric activation layer
  • Flow control layer
  • Wrapper
  • Helper functions
• API - Cost
  • Custom cost function
  • Cost functions
  • Regularization functions
• API - Iteration
  • Non-time series
  • Time series
• API - Utility
  • Training, testing and predicting
  • Evaluation functions
  • Class balancing functions
  • Helper functions
• API - Natural Language Processing
  • Iteration function for training embedding matrix
  • Sampling functions
  • Vector representations of words
  • Functions for translation
• API - Reinforcement Learning
  • Reward functions
  • Cost functions
• API - Load, Save Model and Data
  • Load dataset functions
  • Load and save network
  • Load and save variables
  • Visualizing npz file
  • Helper functions
• API - Visualize Model and Data
  • Visualize model parameters
  • Visualize data
  • Visualize embeddings
• API - Preprocessing
  • Threading
  • Images
  • Sequence
  • Tensor Opt
• API - Operation System
  • TensorFlow functions
  • GPU functions
  • Console display
  • Packages information
  • Trash
• API - Activations
  • Your activation
  • Activation functions

Indices and tables

• Index
• Module Index
• Search Page