class_docstr: Base class for non-interactive (i.e., non-CLI) debug wrapper sessions.
class_docstr_tok: ["Base","class","for","non-interactive","(","i.e.",",","non-CLI",")","debug","wrapper","sessions","."]
docstr: Constructor of NonInteractiveDebugWrapperSession.
  
  Args:
    sess: The TensorFlow `Session` object being wrapped.
    watch_fn: (`Callable`) A Callable that maps the fetches and feeds of a
      debugged `Session.run()` call to `WatchOptions.`
      * Args:
        * `fetches`: the fetches to the `Session.run()` call.
        * `feeds`: the feeds to the `Session.run()` call.
  
      * Returns:
       (`tf_debug.WatchOptions`) An object containing debug options including
         the debug ops to use, the node names, op types and/or tensor data
         types to watch, etc. See the documentation of `tf_debug.WatchOptions`
         for more details.
    thread_name_filter: Regular-expression white list for threads on which the
      wrapper session will be active. See doc of `BaseDebugWrapperSession` for
      more details.
    pass_through_operrors: If true, all captured OpErrors will be
      propagated.  By default this captures all OpErrors.
  Raises:
     TypeError: If a non-None `watch_fn` is specified and it is not callable.
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code: def __init__(
      self,
      sess,
      watch_fn=None,
      thread_name_filter=None,
      pass_through_operrors=False,
  ):
      """Constructor of NonInteractiveDebugWrapperSession.
  
      Args:
        sess: The TensorFlow `Session` object being wrapped.
        watch_fn: (`Callable`) A Callable that maps the fetches and feeds of a
          debugged `Session.run()` call to `WatchOptions.`
          * Args:
            * `fetches`: the fetches to the `Session.run()` call.
            * `feeds`: the feeds to the `Session.run()` call.
  
          * Returns:
           (`tf_debug.WatchOptions`) An object containing debug options including
             the debug ops to use, the node names, op types and/or tensor data
             types to watch, etc. See the documentation of `tf_debug.WatchOptions`
             for more details.
        thread_name_filter: Regular-expression white list for threads on which the
          wrapper session will be active. See doc of `BaseDebugWrapperSession` for
          more details.
        pass_through_operrors: If true, all captured OpErrors will be
          propagated.  By default this captures all OpErrors.
      Raises:
         TypeError: If a non-None `watch_fn` is specified and it is not callable.
      """
  
      BaseDebugWrapperSession.__init__(
          self,
          sess,
          thread_name_filter=thread_name_filter,
          pass_through_operrors=pass_through_operrors,
      )
  
      self._watch_fn = None
      if watch_fn is not None:
          if not callable(watch_fn):
              raise TypeError("watch_fn is not callable")
          self._watch_fn = watch_fn
  
imports: import abc
  import re
  import threading
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.debug.lib import debug_utils
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import stack
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import monitored_session
  from tensorflow.python.util import nest
  from tensorflow.python.util.compat import collections_abc
label_desc: Use image node_id 1 to create a new NonInteractiveDebugWrapperSession object from inherited base classes: BaseDebugWrapperSession with example: obj = NonInteractiveDebugWrapperSession(sess, watch_fn, thread_name_filter, pass_through_operrors)