code: def broadcast(
      tensor, root_rank, scope="", name=None, is_variable=True
  ):
      """An op which broadcasts the input tensor on root rank to the same input tensor
      on all other BytePS processes.
      The broadcast operation is keyed by the name of the op. The tensor type and
      shape must be the same on all BytePS processes for a given name. The broadcast
      will not start until all processes are ready to send and receive the tensor.
      Returns:
        A tensor of the same shape and type as `tensor`, with the value broadcasted
        from root rank.
      """
      # Broadcast is implemented as push + pull after zero-ing non-root tensors
      if name is None and not _executing_eagerly():
          name = "BytePSBroadcast_%s" % _normalize_name(tensor.name)
      if scope == "" and not _executing_eagerly():
          if "v1" in dir(tf.compat):
              scope = tf.compat.v1.get_default_graph().get_name_scope()
          else:
              scope = tf.get_default_graph().get_name_scope()
          if scope != "":
              scope += "/"
      if not name:
          name = ""
      full_name = scope + name
      if not full_name:
          full_name = "empty_name_" + randomString()
      full_name_ascii = full_name.encode("ascii")
  
      TF_LIB_CTYPES.byteps_tensorflow_declare_tensor(
          ctypes.c_char_p(full_name_ascii)
      )
      if root_rank != rank():
          if is_variable:
              if hasattr(tf, "assign_sub"):
                  with tf.control_dependencies(
                      [tf.assign_sub(tensor, tensor)]
                  ):
                      return C_LIB.byteps_push_pull(tensor, name=name)
              else:
                  with tf.control_dependencies(
                      [tf.compat.v1.assign_sub(tensor, tensor)]
                  ):
                      return C_LIB.byteps_push_pull(
                          tensor, name=name, input_name=full_name
                      )
          else:
              with tf.device(tensor.device):
                  input_tensor = tf.zeros_like(tensor)
              return C_LIB.byteps_push_pull(
                  input_tensor, name=name, input_name=full_name
              )
      else:
          return C_LIB.byteps_push_pull(
              tensor, name=name, input_name=full_name
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import re
  import os
  import ctypes
  from enum import Enum
  import random
  import string
  import warnings
  from tensorflow.python.framework import load_library
  from tensorflow.python.framework import ops
  from tensorflow.python.platform import resource_loader
  from byteps.common import get_ext_suffix
  from byteps.common import BytePSBasics
  from byteps.tensorflow.util import _executing_eagerly
  import tensorflow
label_desc: Use image node_id 7 for calling a global function with example usage: broadcast(tensor, root_rank, scope, name, is_variable) and returns: C_LIB, C_LIB, C_LIB, C_LIB