TensorFlow Python reference documentation

haosdent TensorFlow Python reference documentation

Building Graphs

Classes and functions for building TensorFlow graphs.

Asserts and boolean checks

assertion

Constants, Sequences, and Random Values

Constant: 生成Constant Value Tensors的API

Sequences: 生成sequence的API

Random Tensors: 生成random tensors with different distributions的API

Variables

Tensor Transformations

对Tensor进行操作

Math

basic arithmetic operators

Strings

Histograms

直方图

Control Flow

TensorFlow provides several operations and classes that you can use to control the execution of operations and add conditional dependencies to your graph.

Higher Order Functions

TensorFlow provides several higher order operators to simplify the common map-reduce programming patterns

TensorArray Operations

class tf.TensorArray

Tensor Handle Operations

TensorFlow provides several operators that allows the user to keep tensors "in-place" across run calls(允许用户在运行调用时将张量保持在“原位”)

Images

图像进行操作的API

Sparse Tensors

Inputs and Readers

Data IO (Python functions)

feed data的API

Neural Network

tf.nn - Activation Functions - Convolution - Pooling - Morphological filtering - Normalization - Losses - Classification - Embeddings - Recurrent Neural Networks - Connectionist Temporal Classification (CTC) - Evaluation - Candidate Sampling - Other Functions and Classes

Neural Network RNN Cells

Running Graphs

This library contains classes for launching graphs and executing operations.

The basic usage guide has examples of how a graph is launched in a tf.Session.

Training

This library provides a set of classes and functions that helps train models.

Wraps python functions

TensorFlow provides allows you to wrap python/numpy functions as TensorFlow operators.

Summary Operations

This module contains ops for generating summaries.

Testing

TensorFlow provides a convenience class inheriting from unittest.TestCase which adds methods relevant to TensorFlow tests.

BayesFlow Entropy (contrib)

BayesFlow Stochastic Tensors (contrib)

BayesFlow Variational Inference (contrib)

Variational(变分法) inference.

CRF (contrib)

Linear-chain CRF layer.

Statistical distributions (contrib)

Classes representing statistical distributions and ops for working with them.

FFmpeg (contrib)

Encoding and decoding audio using FFmpeg

Framework (contrib)

Graph Editor (contrib)

The TensorFlow Graph Editor library allows for modification of an existing tf.Graph instance in-place.

Layers (contrib)

Ops for building neural network layers, regularizers, summaries, etc.

Learn (contrib)

High level API for learning with TensorFlow.

Monitors (contrib)

Monitors allow user instrumentation of the training process.

Losses (contrib)

Ops for building neural network losses.

RNN (contrib)

Additional RNN operations and cells.

Metrics (contrib)

Ops for evaluation metrics and summary statistics