How to Print the Values of TensorFlow Tensors?

Printing Values of TensorFlow Tensors: A Comprehensive Guide

In TensorFlow, a Tensor object represents a multidimensional array of data. To access the actual values stored within a Tensor, you'll need to evaluate it within a Session.

Session.run() Method

The most straightforward approach is to use the Session.run() method to evaluate the Tensor and retrieve its value:

import tensorflow as tf

sess = tf.Session()
matrix1 = tf.constant([[3., 3.]])
matrix2 = tf.constant([[2.],[2.]])
product = tf.matmul(matrix1, matrix2)
print(sess.run(product))

This will print the value of the Tensor as a NumPy array.

Tensor.eval() Method

You can also use the Tensor.eval() method to evaluate a Tensor within the default Session:

with tf.Session():
    print(product.eval())

Interactive Session

For a more convenient approach, you can use the tf.InteractiveSession to open a default Session for your entire program:

import tensorflow as tf

tf.InteractiveSession()

matrix1 = tf.constant([[3., 3.]])
matrix2 = tf.constant([[2.],[2.]])
product = tf.matmul(matrix1, matrix2)
print(product.eval())

Notes

• For efficiency, TensorFlow separates the definition of computations (building the dataflow graph) from the execution (evaluating the graph and producing values).
• The tf.print() operator can also be used to print the value of a Tensor, but this requires manual execution with Session.run().
• The tf.get_static_value() function can be used to get the constant value of a Tensor if it can be calculated efficiently.

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