code: def from_config(cls, cfg, input_shape):
      s = input_shape
      s = s[0] if isinstance(s, (list, tuple)) else s
      return {"in_channel": s.channels}
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import Normal, XavierUniform, KaimingNormal
  from paddle.regularizer import L2Decay
  from ppdet.core.workspace import register, create
  from .roi_extractor import RoIAlign
  from ..shape_spec import ShapeSpec
  from ..bbox_utils import bbox2delta
  from ..cls_utils import _get_class_default_kwargs
  from ppdet.modeling.layers import ConvNormLayer
label_desc: Use image node_id 2 for calling the XConvNormHead obj's underlying member method code with example usage: obj.from_config(cls, cfg, input_shape) and returns: dict