code: def _build_input_proj_layer(self, backbone_feat_channels):
      self.input_proj = nn.LayerList()
      for in_channels in backbone_feat_channels:
          self.input_proj.append(
              nn.Sequential(
                  (
                      "conv",
                      nn.Conv2D(
                          in_channels,
                          self.hidden_dim,
                          kernel_size=1,
                          bias_attr=False,
                      ),
                  ),
                  (
                      "norm",
                      nn.BatchNorm2D(
                          self.hidden_dim,
                          weight_attr=ParamAttr(
                              regularizer=L2Decay(0.0)
                          ),
                          bias_attr=ParamAttr(regularizer=L2Decay(0.0)),
                      ),
                  ),
              )
          )
      in_channels = backbone_feat_channels[-1]
      for _ in range(self.num_levels - len(backbone_feat_channels)):
          self.input_proj.append(
              nn.Sequential(
                  (
                      "conv",
                      nn.Conv2D(
                          in_channels,
                          self.hidden_dim,
                          kernel_size=3,
                          stride=2,
                          padding=1,
                          bias_attr=False,
                      ),
                  ),
                  (
                      "norm",
                      nn.BatchNorm2D(
                          self.hidden_dim,
                          weight_attr=ParamAttr(
                              regularizer=L2Decay(0.0)
                          ),
                          bias_attr=ParamAttr(regularizer=L2Decay(0.0)),
                      ),
                  ),
              )
          )
          in_channels = self.hidden_dim
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from ppdet.core.workspace import register
  from ..layers import MultiHeadAttention
  from ..heads.detr_head import MLP
  from .deformable_transformer import MSDeformableAttention
  from ..initializer import linear_init_, constant_, xavier_uniform_, normal_, bias_init_with_prob
  from .utils import _get_clones, get_sine_pos_embed, get_contrastive_denoising_training_group, inverse_sigmoid
label_desc: Use image node_id 4 for calling the RTDETRTransformer obj's underlying member method code with example usage: obj._build_input_proj_layer(backbone_feat_channels) without return types