class_docstr: 将多个特征矩阵在channel维度进行concatenate拼接
class_docstr_tok: ["\u5c06\u591a\u4e2a\u7279\u5f81\u77e9\u9635\u5728channel\u7ef4\u5ea6\u8fdb\u884cconcatenate\u62fc\u63a5"]
code: def __init__(self, layers):
      super(FeatureConcat, self).__init__()
      self.layers = layers  # layer indices
      self.multiple = len(layers) > 1
  
imports: import torch.nn.functional
  from .utils import *
label_desc: Use image node_id 1 to create a new FeatureConcat object from inherited base classes: nn with example: obj = FeatureConcat(layers)