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 __init__(
      self,
      feat_in=256,
      feat_out=256,
      num_convs=4,
      norm_type="bn",
      use_dcn=False,
  ):
      super(FCOSFeat, self).__init__()
      self.feat_in = feat_in
      self.feat_out = feat_out
      self.num_convs = num_convs
      self.norm_type = norm_type
      self.cls_subnet_convs = []
      self.reg_subnet_convs = []
      for i in range(self.num_convs):
          in_c = feat_in if i == 0 else feat_out
  
          cls_conv_name = "fcos_head_cls_tower_conv_{}".format(i)
          cls_conv = self.add_sublayer(
              cls_conv_name,
              ConvNormLayer(
                  ch_in=in_c,
                  ch_out=feat_out,
                  filter_size=3,
                  stride=1,
                  norm_type=norm_type,
                  use_dcn=use_dcn,
                  bias_on=True,
                  lr_scale=2.0,
              ),
          )
          self.cls_subnet_convs.append(cls_conv)
  
          reg_conv_name = "fcos_head_reg_tower_conv_{}".format(i)
          reg_conv = self.add_sublayer(
              reg_conv_name,
              ConvNormLayer(
                  ch_in=in_c,
                  ch_out=feat_out,
                  filter_size=3,
                  stride=1,
                  norm_type=norm_type,
                  use_dcn=use_dcn,
                  bias_on=True,
                  lr_scale=2.0,
              ),
          )
          self.reg_subnet_convs.append(reg_conv)
  
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 1 to create a new FCOSFeat object from inherited base classes: nn with example: obj = FCOSFeat(feat_in, feat_out, num_convs, norm_type, use_dcn)