class_docstr: FCOSFeat of FCOS
  
  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 FCOSFeat.
      norm_type (str): Normalization type, 'bn'/'sync_bn'/'gn'.
      use_dcn (bool): Whether to use dcn in tower or not.
code: def forward(self, fpn_feat):
      cls_feat = fpn_feat
      reg_feat = fpn_feat
      for i in range(self.num_convs):
          cls_feat = F.relu(self.cls_subnet_convs[i](cls_feat))
          reg_feat = F.relu(self.reg_subnet_convs[i](reg_feat))
      return cls_feat, reg_feat
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn.initializer import Normal, Constant
  from ppdet.core.workspace import register
  from ppdet.modeling.layers import ConvNormLayer, MultiClassNMS
label_desc: Use image node_id 2 for calling the FCOSFeat obj's underlying member method code with example usage: obj.forward(fpn_feat) and returns: cls_feat,  reg_feat