Welcome to the TensorFlow API documentation. This page provides comprehensive information about the TensorFlow library, including its modules, classes, and functions. Whether you are a beginner or an experienced user, you will find the resources you need to understand and utilize TensorFlow effectively.

Overview

TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is widely used for machine learning and deep learning applications.

Key Modules

Here are some of the key modules available in TensorFlow:

  • Tensor: Represents a tensor, the fundamental data structure in TensorFlow.
  • Graph: Represents a computation graph, which is a series of operations.
  • Session: Executes operations in a graph.

Examples

Let's take a look at a simple example of a TensorFlow operation:

import tensorflow as tf

# Create a simple graph
a = tf.constant(5)
b = tf.constant(6)

# Add the two constants
c = a + b

# Launch the default graph and run the operation
with tf.Session() as sess:
  print(sess.run(c))

This example demonstrates how to create constants, add them together, and execute the operation within a TensorFlow session.

Learning Resources

If you are new to TensorFlow, we recommend the following resources:

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