class_docstr: An object holding the states surrounding the dumping callback.
class_docstr_tok: ["An","object","holding","the","states","surrounding","the","dumping","callback","."]
code: def __init__(
      self,
      dump_root,
      tensor_debug_mode,
      circular_buffer_size,
      op_regex,
      tensor_dtypes,
  ):
      self._dump_root = dump_root
      self._tfdbg_run_id = _get_tfdbg_run_id()
      self._tensor_debug_mode = tensor_debug_mode
      self._circular_buffer_size = circular_buffer_size
      self._op_regex = op_regex
      self._tensor_dtypes = tensor_dtypes
  
      self._hostname = socket.gethostname()
      # A list of source-file paths.
      self._source_file_paths = []
      # A map from stack frame (FileLineCol) to unique ID.
      self._stack_frame_to_id = dict()
      # Mapping op context to unique ID.
      self._context_to_id = dict()
      self._function_to_graph_id = dict()
      self._op_type_to_context_id = dict()
      # Keeps track of counter for symbolic tensors output by in-graph ops.
      # It is used to make unique names for debugger-generated tensors.
      self._symbolic_tensor_counter = 0
      # A map from the names of debugger-generated Identity and DebugIdentityV2
      # tensors to the names of the original insrumented graph tensors. This is
      # applicable to v1 graph mode only.
      self._tensor_aliases = dict()
      self._source_file_paths_lock = threading.Lock()
      self._stack_frame_to_id_lock = threading.Lock()
      self._context_lock = threading.Lock()
      self._symbolic_tensor_counter_lock = threading.Lock()
      # A dict mapping Placeholder tensors to their instrumenting debug tensors.
      # Used only under V1 graph mode, where we can't rely on auto control
      # dependency to execute the debug tensors and hence need to attach the debug
      # tensors as control dependencies of the ops that consume the Placeholder.
      self._placeholder_to_debug_tensor = (
          object_identity.ObjectIdentityDictionary()
      )
      self._writer = None
  
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 1 to create a new _DumpingCallback object from inherited base classes: object with example: obj = _DumpingCallback(dump_root, tensor_debug_mode, circular_buffer_size, op_regex, tensor_dtypes)