class_docstr: Spatial Pyramid Pooling - Fast (SPPF) layer used in YOLOv5 by Glenn Jocher,
  equivalent to SPP(k=(5, 9, 13))
code: def __init__(
      self, in_channels, out_channels, ksize=5, bias=False, act="silu"
  ):
      super(SPPFLayer, self).__init__()
      hidden_channels = in_channels // 2
      self.conv1 = BaseConv(
          in_channels,
          hidden_channels,
          ksize=1,
          stride=1,
          bias=bias,
          act=act,
      )
      self.maxpooling = nn.MaxPool2D(
          kernel_size=ksize, stride=1, padding=ksize // 2
      )
      conv2_channels = hidden_channels * 4
      self.conv2 = BaseConv(
          conv2_channels,
          out_channels,
          ksize=1,
          stride=1,
          bias=bias,
          act=act,
      )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from ppdet.core.workspace import register, serializable
  from ppdet.modeling.initializer import conv_init_
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 1 to create a new SPPFLayer object from inherited base classes: nn with example: obj = SPPFLayer(in_channels, out_channels, ksize, bias, act)