code: def make_linear_from_emb(emb):
      vocab_size, emb_size = emb.weight.shape
      lin_layer = nn.Linear(vocab_size, emb_size, bias=False)
      lin_layer.weight.data = emb.weight.data
      return lin_layer
  
file_path: transformers/src/transformers/models/speech_encoder_decoder/convert_mbart_wav2vec2_seq2seq_original_to_pytorch.py
imports: import argparse
  import fairseq
  import torch
  from torch import nn
  from transformers import MBart50Tokenizer, MBartConfig, MBartForCausalLM, SpeechEncoderDecoderConfig, SpeechEncoderDecoderModel, Wav2Vec2Config, Wav2Vec2FeatureExtractor, Wav2Vec2Model, logging
label_desc: Use image node_id 5 for calling a global function with example usage: make_linear_from_emb(emb) and returns: lin_layer