class_docstr: Abstract class for TensorFlow model loader.
class_docstr_tok: ["Abstract","class","for","TensorFlow","model","loader","."]
docstr: Load TensorFlow model into MIL program.
docstr_tok: ["Load","TensorFlow","model","into","MIL","program","."]
code: def load(self):
      """Load TensorFlow model into MIL program."""
  
      logging.info("Loading TensorFlow model '{}'".format(self.model))
      outputs = self.kwargs.get("outputs", None)
      self._graph_def = self._graph_def_from_model(outputs)
  
      if self._graph_def is not None and len(self._graph_def.node) == 0:
          msg = "tf.Graph should have at least 1 node, Got empty graph."
          raise ValueError(msg)
  
      self._tf_ssa = self._tf_ssa_from_graph_def()
  
      del self._graph_def
      gc.collect()
  
      if self.debug:
          import graphviz
  
          dot_string = self._tf_ssa.get_dot_string(
              annotation=True,
              name_and_op_style=True,
              highlight_debug_nodes=[],
          )
          graphviz.Source(dot_string).view(
              filename="/tmp/ssa_before_tf_passes", cleanup=True
          )
  
      program = self._program_from_tf_ssa()
      logging.debug("program:\n{}".format(program))
      return program
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import logging
  import os
  import gc
  import six
  import tensorflow
  from tempfile import mktemp
  from .basic_graph_ops import fill_outputs
  from .converter import TFConverter
  from .tf_graph_pass import *
  from .tfssa import NetworkEnsemble, SSAFunction
  from .parsed_tf_node import ParsedTFNode
  from coremltools.converters._profile_utils import _profile
  from tqdm import tqdm
  from distutils.version import StrictVersion
label_desc: Use image node_id 2 for calling the TFLoader obj's underlying member method code with example usage: obj.load() and returns: program