class_docstr: Data ingestion implementation to use when running locally.
docstr: Initializes a `LocalDataIngester` from `flags`.
  
  Args:
    flags: An argparse.Namespace containing TensorBoard CLI flags.
  
  Returns:
    The new `LocalDataIngester`.
docstr_tok: ["Initializes","a","`","LocalDataIngester","`","from","`","flags","`",".","Args",":","flags",":","An","argparse.Namespace","containing","TensorBoard","CLI","flags",".","Returns",":","The","new","`","LocalDataIngester","`","."]
code: def __init__(self, flags):
      """Initializes a `LocalDataIngester` from `flags`.
  
      Args:
        flags: An argparse.Namespace containing TensorBoard CLI flags.
  
      Returns:
        The new `LocalDataIngester`.
      """
      tensor_size_guidance = dict(DEFAULT_TENSOR_SIZE_GUIDANCE)
      tensor_size_guidance.update(flags.samples_per_plugin)
      self._multiplexer = plugin_event_multiplexer.EventMultiplexer(
          size_guidance=DEFAULT_SIZE_GUIDANCE,
          tensor_size_guidance=tensor_size_guidance,
          purge_orphaned_data=flags.purge_orphaned_data,
          max_reload_threads=flags.max_reload_threads,
          event_file_active_filter=_get_event_file_active_filter(flags),
          detect_file_replacement=flags.detect_file_replacement,
      )
      self._data_provider = data_provider.MultiplexerDataProvider(
          self._multiplexer, flags.logdir or flags.logdir_spec
      )
      self._reload_interval = flags.reload_interval
      self._reload_task = flags.reload_task
      if flags.logdir:
          self._path_to_run = {os.path.expanduser(flags.logdir): None}
      else:
          self._path_to_run = _parse_event_files_spec(flags.logdir_spec)
  
      # Conditionally import tensorflow_io.
      if getattr(tf, "__version__", "stub") != "stub":
          _check_filesystem_support(self._path_to_run.keys())
  
imports: import os
  import re
  import threading
  import time
  from tensorboard.backend.event_processing import data_provider
  from tensorboard.backend.event_processing import plugin_event_multiplexer
  from tensorboard.backend.event_processing import tag_types
  from tensorboard.compat import tf
  from tensorboard.data import ingester
  from tensorboard.plugins.audio import metadata
  from tensorboard.plugins.histogram import metadata
  from tensorboard.plugins.image import metadata
  from tensorboard.plugins.pr_curve import metadata
  from tensorboard.plugins.scalar import metadata
  from tensorboard.util import tb_logging
label_desc: Use image node_id 1 to create a new LocalDataIngester object from inherited base classes: ingester with example: obj = LocalDataIngester(flags)