class_docstr: Base class that projects image representations to the same space as text representations
class_docstr_tok: ["Base","class","that","projects","image","representations","to","the","same","space","as","text","representations"]
code: def get_trainable_parameters(
      self,
      weight_decay: Optional[float] = 0.0,
      no_decay_bn_filter_bias: Optional[bool] = False,
      *args,
      **kwargs,
  ):
      param_list = parameter_list(
          named_parameters=self.named_parameters,
          weight_decay=weight_decay,
          no_decay_bn_filter_bias=no_decay_bn_filter_bias,
      )
      return param_list, [self.lr_mult] * len(param_list)
  
file_path: ml-cvnets/cvnets/image_projection_layers/base_image_projection.py
imports: import argparse
  from typing import Dict, Optional
  from torch import nn
  from cvnets.layers import LinearLayer
  from cvnets.misc.common import parameter_list
label_desc: Use image node_id 4 for calling the BaseImageProjectionHead obj's underlying member method code with example usage: obj.get_trainable_parameters(weight_decay, no_decay_bn_filter_bias) and returns: param_list,  unknown