code: def remove_projection_matrices(model_file: str):
      """
      Remove all projection matrices used for distillation from the model and re-save it.
      """
  
      print(
          f"Creating a backup copy of the original model at {model_file}._orig."
      )
      PathManager.copy(model_file, f"{model_file}._orig")
  
      print(f"Loading {model_file}.")
      with PathManager.open(model_file, "rb") as f:
          states = torch.load(
              f, map_location=lambda cpu, _: cpu, pickle_module=pickle
          )
  
      print("Deleting projection matrices.")
      orig_num_keys = len(states["model"])
      states["model"] = {
          key: val
          for key, val in states["model"].items()
          if key.split(".")[0]
          not in [
              "encoder_proj_layer",
              "embedding_proj_layers",
              "hidden_proj_layers",
          ]
      }
      new_num_keys = len(states["model"])
      print(f"{orig_num_keys-new_num_keys:d} model keys removed.")
  
      print(f"Saving to {model_file}.")
      atomic_save(states, model_file)
  
imports: import argparse
  import torch
  from parlai.utils import pickle
  from parlai.utils.io import PathManager
  from parlai.utils.torch import atomic_save
label_desc: Use image node_id 1 for calling a global function with example usage: remove_projection_matrices(model_file) without return types