class_docstr: Single layer of a DenseNet.
code: def forward(self, x):
      new_features = super(_DenseLayer, self).forward(x)
      return torch.cat([x, new_features], 1)
  
imports: import math
  from collections import OrderedDict
  from typing import Any, Dict, Sequence
  import torch
  import torch.nn
  from classy_vision.generic.util import is_pos_int
  from .None import register_model
  from .classy_model import ClassyModel
  from .squeeze_and_excitation_layer import SqueezeAndExcitationLayer
label_desc: Use image node_id 2 for calling the _DenseLayer obj's underlying member method code with example usage: obj.forward(x) and returns: torch