class_docstr: Class orientation
  
  Args:
  
      params(dict): super parameters for build Class network
class_docstr_tok: ["Class","orientation","Args",":","params","(","dict",")",":","super","parameters","for","build","Class","network"]
code: def __init__(self, in_channels, class_dim, **kwargs):
      super(ClsHead, self).__init__()
      self.pool = nn.AdaptiveAvgPool2D(1)
      stdv = 1.0 / math.sqrt(in_channels * 1.0)
      self.fc = nn.Linear(
          in_channels,
          class_dim,
          weight_attr=ParamAttr(
              name="fc_0.w_0",
              initializer=nn.initializer.Uniform(-stdv, stdv),
          ),
          bias_attr=ParamAttr(name="fc_0.b_0"),
      )
  
file_path: PaddleOCR/ppocr/modeling/heads/cls_head.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import nn, ParamAttr
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new ClsHead object from inherited base classes: nn with example: obj = ClsHead(in_channels, class_dim)