class_docstr: the MicroNet backbone network for recognition module.
  Args:
      mode(str): {'M0', 'M1', 'M2', 'M3'} 
          Four models are proposed based on four different computational costs (4M, 6M, 12M, 21M MAdds)
          Default: 'M3'.
class_docstr_tok: ["the","MicroNet","backbone","network","for","recognition","module",".","Args",":","mode","(","str",")",":","{","'M0","'",",","'M1","'",",","'M2","'",",","'M3","'","}","Four","models","are","proposed","based","on","four","different","computational","costs","(","4M",",","6M",",","12M",",","21M","MAdds",")","Default",":","'M3","'","."]
code: def forward(self, x):
      x = self.features(x)
      x = self.pool(x)
      return x
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  from ppocr.modeling.backbones.det_mobilenet_v3 import make_divisible
label_desc: Use image node_id 2 for calling the MicroNet obj's underlying member method code with example usage: obj.forward(x) and returns: x