class_docstr: An object holding the states surrounding the dumping callback.
class_docstr_tok: ["An","object","holding","the","states","surrounding","the","dumping","callback","."]
docstr: For V1 graph mode, determine what tensor to output from callback.
  
  Args:
    op_type: Type of the op that outputs the original symbolic tensor.
    tensor: The original output symbolic tensor.
    debug_tensor: The debugger-instrumented tensor.
    tensor_debug_mode: Debug mode used, a tfdbg TensorDebugMode enum.
  
  Returns:
    A symbolic tensor to be returned by the dumping op_callback.
code: def _process_v1_graph_mode_tensor(
      self, op_type, tensor, debug_tensor, tensor_debug_mode
  ):
      """For V1 graph mode, determine what tensor to output from callback.
  
      Args:
        op_type: Type of the op that outputs the original symbolic tensor.
        tensor: The original output symbolic tensor.
        debug_tensor: The debugger-instrumented tensor.
        tensor_debug_mode: Debug mode used, a tfdbg TensorDebugMode enum.
  
      Returns:
        A symbolic tensor to be returned by the dumping op_callback.
      """
      # Placeholders need special treatment under V1 graph mode. The
      # callback can't simply override the Placeholder tensor to a debug tensor,
      # as that would cause the Placeholder op to lack a value.
      if op_type in ("Placeholder", "PlaceholderWithDefault"):
          self._placeholder_to_debug_tensor[tensor] = debug_tensor
          return tensor
      else:
          # TODO(cais): Evaluate performance optimization options. For the
          # `NO_TENSOR` debug mode, an alternative is to add `debug_tensor` as a
          # control dependency of `tensor.op` without an additional identity op.
          if (
              tensor_debug_mode
              == debug_event_pb2.TensorDebugMode.FULL_TENSOR
              and op_type != "Const"
          ):
              # NOTE(b/153716279): Under v1 graph mode, overriding the output tensor
              # of Const ops can lead to downstream errors related to shapes. We opt
              # to use an identity op to avoid this issue at the cost of slightly
              # larger graph size.
              self._tensor_aliases[debug_tensor.name] = tensor.name
              return debug_tensor
          else:
              with self._symbolic_tensor_counter_lock:
                  identity_name = (
                      "tfdbg_identity_%d"
                      % self._symbolic_tensor_counter
                  )
              identity = array_ops.identity(tensor, name=identity_name)
              identity.op._add_control_input(  # pylint: disable=protected-access
                  debug_tensor.op
              )
              self._tensor_aliases[identity.name] = tensor.name
              return identity
  
imports: import atexit
  import os
  import re
  import socket
  import threading
  import uuid
  from tensorflow.core.framework import graph_debug_info_pb2
  from tensorflow.core.framework import tensor_pb2
  from tensorflow.core.protobuf import debug_event_pb2
  from tensorflow.python.debug.lib import debug_events_writer
  from tensorflow.python.debug.lib import op_callbacks_common
  from tensorflow.python.debug.lib import source_utils
  from tensorflow.python.eager import function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import op_callbacks
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_debug_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import compat
  from tensorflow.python.util import object_identity
  from tensorflow.python.util import tf_stack
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 13 for calling the _DumpingCallback obj's underlying member method code with example usage: obj._process_v1_graph_mode_tensor(op_type, tensor, debug_tensor, tensor_debug_mode) and returns: tensor, debug_tensor, identity