class_docstr: Path Aggregation Network with CSP module.
  
  Args:
      in_channels (List[int]): Number of input channels per scale.
      out_channels (int): Number of output channels (used at each scale)
      kernel_size (int): The conv2d kernel size of this Module.
      num_features (int): Number of output features of CSPPAN module.
      num_csp_blocks (int): Number of bottlenecks in CSPLayer. Default: 1
      use_depthwise (bool): Whether to depthwise separable convolution in
          blocks. Default: True
code: def from_config(cls, cfg, input_shape):
      return {
          "in_channels": [i.channels for i in input_shape],
      }
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register, serializable
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 4 for calling the CSPPAN obj's underlying member method code with example usage: obj.from_config(cls, cfg, input_shape) and returns: dict