class_docstr: Args:
      in_channels (list): number of input feature channels from backbone.
          [128,256,512,1024] by default, means the channels of DarkNet53
          backbone return_idx [1,2,3,4].
      planes (list): the number of output feature channels of FPN.
          [256, 128, 64] by default
      shortcut_num (list): the number of convolution layers in each shortcut.
          [3,2,1] by default, means DarkNet53 backbone return_idx_1 has 3 convs
          in its shortcut, return_idx_2 has 2 convs and return_idx_3 has 1 conv.
      norm_type (string): norm type, 'sync_bn', 'bn', 'gn' are optional. 
          bn by default
      lite_neck (bool): whether to use lite conv in TTFNet FPN, 
          False by default
      fusion_method (string): the method to fusion upsample and lateral layer.
          'add' and 'concat' are optional, add by default
class_docstr_tok: ["Args",":","in_channels","(","list",")",":","number","of","input","feature","channels","from","backbone",".","[","128,256,512,1024","]","by","default",",","means","the","channels","of","DarkNet53","backbone","return_idx","[","1,2,3,4","]",".","planes","(","list",")",":","the","number","of","output","feature","channels","of","FPN",".","[","256",",","128",",","64","]","by","default","shortcut_num","(","list",")",":","the","number","of","convolution","layers","in","each","shortcut",".","[","3,2,1","]","by","default",",","means","DarkNet53","backbone","return_idx_1","has","3","convs","in","its","shortcut",",","return_idx_2","has","2","convs","and","return_idx_3","has","1","conv",".","norm_type","(","string",")",":","norm","type",",","'sync_bn","'",",","'bn","'",",","'gn","'","are","optional",".","bn","by","default","lite_neck","(","bool",")",":","whether","to","use","lite","conv","in","TTFNet","FPN",",","False","by","default","fusion_method","(","string",")",":","the","method","to","fusion","upsample","and","lateral","layer",".","'add","'","and","'concat","'","are","optional",",","add","by","default"]
code: def out_shape(self):
      return [
          ShapeSpec(
              channels=self.upper_list[-1],
          )
      ]
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn.initializer import Constant, Uniform, Normal, XavierUniform
  from ppdet.core.workspace import register, serializable
  from paddle.regularizer import L2Decay
  from ppdet.modeling.layers import DeformableConvV2, ConvNormLayer, LiteConv
  import math
  from ppdet.modeling.ops import batch_norm
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 4 for calling the TTFFPN obj's underlying member method code with example usage: obj.out_shape() and returns: list