docstr: TensorFlow 1.x model loader.
  
  Parameters
  ----------
  model: Model created with TensorFlow 1.x
      One of the following model format:
          - TensorFlow tf.Graph object or frozen graph (.pb) file path
          - TensorFlow tf.keras.Model object or HDF5 (.h5) file path
          - TensorFlow SavedModel directory path
  debug: bool, optional. Defaults to False.
      This flag should generally be False except for debugging purposes
      for diagnosing conversion errors. Setting this flag to True will
      cause graph pass errors to be ignored, forcefully returning a
      NetworkEnsemble object.
  kwargs: dict(str, Any), optional
      Dictionary of additional arguments.
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code: def __init__(self, model, debug=False, **kwargs):
      """
      TensorFlow 1.x model loader.
  
      Parameters
      ----------
      model: Model created with TensorFlow 1.x
          One of the following model format:
              - TensorFlow tf.Graph object or frozen graph (.pb) file path
              - TensorFlow tf.keras.Model object or HDF5 (.h5) file path
              - TensorFlow SavedModel directory path
      debug: bool, optional. Defaults to False.
          This flag should generally be False except for debugging purposes
          for diagnosing conversion errors. Setting this flag to True will
          cause graph pass errors to be ignored, forcefully returning a
          NetworkEnsemble object.
      kwargs: dict(str, Any), optional
          Dictionary of additional arguments.
      """
      TFLoader.__init__(self, model, debug, **kwargs)
  
imports: import gc
  import os
  from distutils.version import StrictVersion
  from tempfile import mktemp
  import tensorflow
  from tqdm import tqdm
  from coremltools import _logger
  from coremltools._deps import _get_version
  from coremltools.converters._profile_utils import _profile
  from .._utils import get_output_names
  from .basic_graph_ops import fill_outputs
  from .converter import TFConverter
  from .parsed_tf_node import ParsedTFNode
  from .tf_graph_pass import cond_to_where, constant_propagation, delete_asserts, delete_disconnected_nodes, delete_unnecessary_constant_nodes, functionalize_loops, fuse_dilation_conv, insert_get_tuple, quantization_pass, remove_variable_nodes, tensor_array_resource_removal
  from .tfssa import NetworkEnsemble, SSAFunction
label_desc: Use image node_id 1 to create a new TF1Loader object from inherited base classes: TFLoader with example: obj = TF1Loader(model, debug)