content: import argparse
  
  from mmcv import Config
  
  from mmaction.models import build_recognizer
  
  try:
      from mmcv.cnn import get_model_complexity_info
  except ImportError:
      raise ImportError('Please upgrade mmcv to >0.6.2')
  
  
  def parse_args():
      parser = argparse.ArgumentParser(description='Train a recognizer')
      parser.add_argument('config', help='train config file path')
      parser.add_argument(
          '--shape',
          type=int,
          nargs='+',
          default=[340, 256],
          help='input image size')
      args = parser.parse_args()
      return args
  
  
  def main():
  
      args = parse_args()
  
      if len(args.shape) == 1:
          input_shape = (1, 3, args.shape[0], args.shape[0])
      elif len(args.shape) == 2:
          input_shape = (
              1,
              3,
          ) + tuple(args.shape)
      elif len(args.shape) == 4:
          # n, c, h, w = args.shape
          input_shape = tuple(args.shape)
      elif len(args.shape) == 5:
          # n, c, t, h, w = args.shape
          input_shape = tuple(args.shape)
      else:
          raise ValueError('invalid input shape')
  
      cfg = Config.fromfile(args.config)
      model = build_recognizer(
          cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)
      model = model.cuda()
      model.eval()
  
      if hasattr(model, 'forward_dummy'):
          model.forward = model.forward_dummy
      else:
          raise NotImplementedError(
              'FLOPs counter is currently not currently supported with {}'.
              format(model.__class__.__name__))
  
      flops, params = get_model_complexity_info(model, input_shape)
      split_line = '=' * 30
      print(f'{split_line}\nInput shape: {input_shape}\n'
            f'Flops: {flops}\nParams: {params}\n{split_line}')
      print('!!!Please be cautious if you use the results in papers. '
            'You may need to check if all ops are supported and verify that the '
            'flops computation is correct.')
  
  
  if __name__ == '__main__':
      main()
  