def __init__()

in src/neuron-gatherinfo/tf_neuron_check_model.py [0:0]

• 24 lines of code
• 5 McCabe index (conditional complexity)

  def __init__(self):
    self.parser = argparse.ArgumentParser()
    self.parser.add_argument('model_path', type=str, help='a TensorFlow SavedModel directory (currently supporting TensorFlow v1 SaveModel only).')
    self.parser.add_argument('--show_names', action='store_true', help='list operation by name instead of summarizing by type (caution: this option will generate many lines of output for a large model).')
    self.parser.add_argument('--expand_subgraph', action='store_true', help='show subgraph operations.')
    self.parser_args = self.parser.parse_args()
    self.neuronop_info = {}
    self.total_pipeline_cores = 0
    self.min_required_pipeline_cores = 0
    path = self.parser_args.model_path
    if os.path.exists(path + '-symbol.json'):
      self.load_mxnet_model(path)
    elif os.path.isdir(path):
      self.load_tensorflow_model(path)
    else:
      raise RuntimeError('Cannot determine framework type from model path argument.')
    self.supported = self.get_neuron_supported()
    self.supported.extend(self.addl_support)
    for name, executable, (sg_nodetypes, sg_nodenames) in self.neuron_nodes:
      num_cores, requested_cores, _ = self.get_cores_from_executable(executable)
      self.neuronop_info[name] = (num_cores, requested_cores, sg_nodetypes, sg_nodenames)
      self.total_pipeline_cores += num_cores
      if num_cores > self.min_required_pipeline_cores:
          self.min_required_pipeline_cores = num_cores