code: def _init_feature_projectors(self, attr):
      feature_projectors = []
      feat_encoders_list_config = self.config[
          attr + "_feature_projections"
      ]
      feat_dim = getattr(self, attr + "_feature_dim")
  
      for feat_encoder in feat_encoders_list_config:
          feat_encoder_config = copy.deepcopy(feat_encoder)
          feat_encoder_config.params.in_dim = feat_dim
          feat_model = build_image_encoder(
              feat_encoder_config, direct_features=True
          )
  
          feature_projectors.append(feat_model)
          setattr(self, attr + "_feature_dim", feat_model.out_dim)
  
      setattr(
          self,
          attr + "_feature_projectors",
          nn.ModuleList(feature_projectors),
      )
  
imports: import copy
  import omegaconf
  import torch
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.embeddings import ImageFeatureEmbedding, MultiHeadImageFeatureEmbedding, PreExtractedEmbedding, TextEmbedding
  from mmf.modules.layers import ClassifierLayer, ModalCombineLayer
  from mmf.utils.build import build_image_encoder
  from torch import nn
label_desc: Use image node_id 4 for calling the PythiaMultiHead obj's underlying member method code with example usage: obj._init_feature_projectors(attr) without return types