tf.Print

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

Defined in tensorflow/python/ops/logging_ops.py.

Prints a list of tensors. (deprecated)

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:

    sess = tf.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`


This is an identity op (behaves like <a href="../tf/identity"><code>tf.identity</code></a>) 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:

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


#### Returns:

A `Tensor`. Has the same type and contents as `input_`.