tf.Print

Prints a list of tensors. (deprecated)

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.Print

tf.Print(
    input_, data, message=None, first_n=None, summarize=None, name=None
)

Warning: THIS FUNCTION IS DEPRECATED. It will be removed after 2018-08-20. Instructions for updating: Use tf.print instead of tf.Print. Note that tf.print returns a no-output operator that directly prints the output. Outside of defuns or eager mode, this operator will not be executed unless it is directly specified in session.run or used as a control dependency for other operators. This is only a concern in graph mode. Below is an example of how to ensure tf.print executes in graph mode:

This is an identity op (behaves like tf.identity) with the side effect of printing data when evaluating.

Note: This op prints to the standard error. It is not currently compatible with jupyter notebook (printing to the notebook server's output, not into the notebook).

Args
input_	A tensor passed through this op.
data	A list of tensors to print out when op is evaluated.
message	A string, prefix of the error message.
first_n	Only log first_n number of times. Negative numbers log always; this is the default.
summarize	Only print this many entries of each tensor. If None, then a maximum of 3 elements are printed per input tensor.
name	A name for the operation (optional).

Returns
A Tensor. Has the same type and contents as input_. sess = tf.compat.v1.Session() with sess.as_default(): tensor = tf.range(10) print_op = tf.print(tensor) with tf.control_dependencies([print_op]): out = tf.add(tensor, tensor) sess.run(out) Additionally, to use tf.print in python 2.7, users must make sure to import the following:

from __future__ import print_function