code: def Print(
      input_,
      data,
      message=None,
      first_n=None,
      summarize=None,
      name=None,
  ):
      """Prints a list of tensors.
  
      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).
  
      @compatibility(TF2)
      This API is deprecated. Use `tf.print` instead. `tf.print` does not need the
      `input_` argument.
  
      `tf.print` works in TF2 when executing eagerly and inside a `tf.function`.
  
      In TF1-styled sessions, an explicit control dependency declaration is needed
      to execute the `tf.print` operation. Refer to the documentation of
      `tf.print` for more details.
      @end_compatibility
  
      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_`.
  
        ```python
        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)
        ```
      """
      return gen_logging_ops._print(
          input_, data, message, first_n, summarize, name
      )
  
imports: import collections
  import os
  import pprint
  import random
  import sys
  from absl import logging
  from tensorflow.python import pywrap_tfe
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import gen_logging_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.gen_logging_ops import *
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import dispatch
  from tensorflow.python.util import nest
  from tensorflow.python.util.deprecation import deprecated
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling a global function with example usage: Print(input_, data, message, first_n, summarize, name) and returns: gen_logging_ops