[PyTorch Bart] Split Bart into different models (#9343)

* first try

* remove old template

* finish bart

* finish mbart

* delete unnecessary line

* init pegasus

* save intermediate

* correct pegasus

* finish pegasus

* remove cookie cutter leftover

* add marian

* finish blenderbot

* replace in file

* correctly split blenderbot

* delete "old" folder

* correct "add statement"

* adapt config for tf comp

* correct configs for tf

* remove ipdb

* fix more stuff

* fix mbart

* push pegasus fix

* fix mbart

* more fixes

* fix research projects code

* finish docs for bart, mbart, and marian

* delete unnecessary file

* correct attn typo

* correct configs

* remove pegasus for seq class

* correct peg docs

* correct peg docs

* finish configs

* further improve docs

* add copied from statements to mbart

* fix copied from in mbart

* add copy statements to marian

* add copied from to marian

* add pegasus copied from

* finish pegasus

* finish copied from

* Apply suggestions from code review

* make style

* backward comp blenderbot

* apply lysandres and sylvains suggestions

* apply suggestions

* push last fixes

* fix docs

* fix tok tests

* fix imports code style

* fix doc

examples/seq2seq/test_datasets.py

@@ -23,7 +23,7 @@ from pack_dataset import pack_data_dir
 from parameterized import parameterized
 from save_len_file import save_len_file
 from transformers import AutoTokenizer
-from transformers.models.bart.modeling_bart import shift_tokens_right
+from transformers.models.mbart.modeling_mbart import shift_tokens_right
 from transformers.testing_utils import TestCasePlus, require_torch_non_multi_gpu_but_fix_me, slow
 from utils import FAIRSEQ_AVAILABLE, DistributedSortishSampler, LegacySeq2SeqDataset, Seq2SeqDataset
 

examples/seq2seq/utils.py

@@ -33,9 +33,8 @@ from torch import nn
 from torch.utils.data import Dataset, Sampler
 
 from sentence_splitter import add_newline_to_end_of_each_sentence
-from transformers import BartTokenizer, EvalPrediction, PreTrainedTokenizer, T5Tokenizer
+from transformers import BartTokenizer, EvalPrediction, PreTrainedTokenizer
 from transformers.file_utils import cached_property
-from transformers.models.bart.modeling_bart import shift_tokens_right
 
 
 try:
@@ -305,15 +304,9 @@ class Seq2SeqDataCollator:
             labels = trim_batch(labels, self.pad_token_id)
             input_ids, attention_mask = trim_batch(input_ids, self.pad_token_id, attention_mask=attention_mask)
 
-        if isinstance(self.tokenizer, T5Tokenizer):
-            decoder_input_ids = self._shift_right_t5(labels)
-        else:
-            decoder_input_ids = shift_tokens_right(labels, self.pad_token_id)
-
         batch = {
             "input_ids": input_ids,
             "attention_mask": attention_mask,
-            "decoder_input_ids": decoder_input_ids,
             "labels": labels,
         }
         return batch