class_docstr: PicoFeat of PicoDet
  
  Args:
      feat_in (int): The channel number of input Tensor.
      feat_out (int): The channel number of output Tensor.
      num_convs (int): The convolution number of the LiteGFLFeat.
      norm_type (str): Normalization type, 'bn'/'sync_bn'/'gn'.
      share_cls_reg (bool): Whether to share the cls and reg output.
      act (str): The act of per layers.
      use_se (bool): Whether to use se module.
class_docstr_tok: ["PicoFeat","of","PicoDet","Args",":","feat_in","(","int",")",":","The","channel","number","of","input","Tensor",".","feat_out","(","int",")",":","The","channel","number","of","output","Tensor",".","num_convs","(","int",")",":","The","convolution","number","of","the","LiteGFLFeat",".","norm_type","(","str",")",":","Normalization","type",",","'bn'\/'sync_bn'\/'gn","'",".","share_cls_reg","(","bool",")",":","Whether","to","share","the","cls","and","reg","output",".","act","(","str",")",":","The","act","of","per","layers",".","use_se","(","bool",")",":","Whether","to","use","se","module","."]
code: def forward(self, fpn_feat, stage_idx):
      assert stage_idx < len(self.cls_convs)
      cls_feat = fpn_feat
      reg_feat = fpn_feat
      for i in range(len(self.cls_convs[stage_idx])):
          cls_feat = self.act_func(
              self.cls_convs[stage_idx][i](cls_feat)
          )
          reg_feat = cls_feat
          if not self.share_cls_reg:
              reg_feat = self.act_func(
                  self.reg_convs[stage_idx][i](reg_feat)
              )
      if self.use_se:
          avg_feat = F.adaptive_avg_pool2d(cls_feat, (1, 1))
          se_feat = self.act_func(
              self.se[stage_idx](cls_feat, avg_feat)
          )
          return cls_feat, se_feat
      return cls_feat, reg_feat
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn.initializer import Normal, Constant
  from ppdet.modeling.ops import get_static_shape
  from ..initializer import normal_
  from ..assigners.utils import generate_anchors_for_grid_cell
  from ..bbox_utils import bbox_center, batch_distance2bbox, bbox2distance
  from ppdet.core.workspace import register
  from ppdet.modeling.layers import ConvNormLayer
  from .simota_head import OTAVFLHead
  from .gfl_head import Integral, GFLHead
  from ppdet.modeling.necks.csp_pan import DPModule
label_desc: Use image node_id 3 for calling the PicoFeat obj's underlying member method code with example usage: obj.forward(fpn_feat, stage_idx) and returns: cls_feat,  reg_feat, cls_feat,  se_feat