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