Fix bart conversion script (#9923)

* fix conversion script

* typo

* import nn

src/transformers/models/bart/convert_bart_original_pytorch_checkpoint_to_pytorch.py

@@ -22,6 +22,7 @@ from pathlib import Path
 import fairseq
 import torch
 from packaging import version
+from torch import nn
 
 from transformers import (
     BartConfig,
@@ -30,7 +31,6 @@ from transformers import (
     BartModel,
     BartTokenizer,
 )
-from transformers.models.bart.modeling_bart import _make_linear_from_emb
 from transformers.utils import logging
 
 
@@ -78,6 +78,13 @@ def load_xsum_checkpoint(checkpoint_path):
     return hub_interface
 
 
+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
+
+
 @torch.no_grad()
 def convert_bart_checkpoint(checkpoint_path, pytorch_dump_folder_path, hf_checkpoint_name=None):
     """
@@ -119,7 +126,7 @@ def convert_bart_checkpoint(checkpoint_path, pytorch_dump_folder_path, hf_checkp
             model = BartForConditionalGeneration(config).eval()  # an existing summarization ckpt
             model.model.load_state_dict(state_dict)
             if hasattr(model, "lm_head"):
-                model.lm_head = _make_linear_from_emb(model.model.shared)
+                model.lm_head = make_linear_from_emb(model.model.shared)
             new_model_outputs = model.model(tokens)[0]
 
     # Check results