parameters: (pretrained_path=None,**kwargs)
return_statement: return model
docstring: Constructs a MobileNetV3-Large models
docstring_summary: Constructs a MobileNetV3-Large models
docstring_tokens: Constructs a MobileNetV3 - Large models
function: def mobilenetv3_large(pretrained_path=None,**kwargs):
      """
      Constructs a MobileNetV3-Large models
      """
      cfgs = [
          # k, t, c, SE, HS, s
          [3,   1,  16, 0, 0, 1],
          [3,   4,  24, 0, 0, 2],
          [3,   3,  24, 0, 0, 1],
          [5,   3,  40, 1, 0, 2],
          [5,   3,  40, 1, 0, 1],
          [5,   3,  40, 1, 0, 1],
          [3,   6,  80, 0, 1, 2],
          [3, 2.5,  80, 0, 1, 1],
          [3, 2.3,  80, 0, 1, 1],
          [3, 2.3,  80, 0, 1, 1],
          [3,   6, 112, 1, 1, 1],
          [3,   6, 112, 1, 1, 1],
          [5,   6, 160, 1, 1, 2],
          # [5,   6, 160, 1, 1, 1],
          # [5,   6, 160, 1, 1, 1]
      ]
      feat_id = [5,11,12]
      model = MobileNetV3(cfgs, mode='large', feat_id=feat_id, **kwargs)
      if pretrained_path is not None:
          state_dict = torch.load(pretrained_path)
          load_model(model, state_dict)
      return model
function_tokens: def mobilenetv3_large ( pretrained_path = None , * * kwargs ) : cfgs = [ # k, t, c, SE, HS, s [ 3 , 1 , 16 , 0 , 0 , 1 ] , [ 3 , 4 , 24 , 0 , 0 , 2 ] , [ 3 , 3 , 24 , 0 , 0 , 1 ] , [ 5 , 3 , 40 , 1 , 0 , 2 ] , [ 5 , 3 , 40 , 1 , 0 , 1 ] , [ 5 , 3 , 40 , 1 , 0 , 1 ] , [ 3 , 6 , 80 , 0 , 1 , 2 ] , [ 3 , 2.5 , 80 , 0 , 1 , 1 ] , [ 3 , 2.3 , 80 , 0 , 1 , 1 ] , [ 3 , 2.3 , 80 , 0 , 1 , 1 ] , [ 3 , 6 , 112 , 1 , 1 , 1 ] , [ 3 , 6 , 112 , 1 , 1 , 1 ] , [ 5 , 6 , 160 , 1 , 1 , 2 ] , # [5,   6, 160, 1, 1, 1], # [5,   6, 160, 1, 1, 1] ] feat_id = [ 5 , 11 , 12 ] model = MobileNetV3 ( cfgs , mode = 'large' , feat_id = feat_id , * * kwargs ) if pretrained_path is not None : state_dict = torch . load ( pretrained_path ) load_model ( model , state_dict ) return model