[s2s] add src_lang kwarg for distributed eval (#7300)

examples/seq2seq/run_distributed_eval.py

@@ -38,6 +38,9 @@ def eval_data_dir(
     fp16=False,
     task="summarization",
     local_rank=None,
+    src_lang=None,
+    tgt_lang=None,
+    prefix="",
     **generate_kwargs,
 ) -> Dict:
     """Run evaluation on part of the data for one gpu and save to {save_dir}/rank_{rank}_output.json"""
@@ -57,6 +60,8 @@ def eval_data_dir(
     use_task_specific_params(model, task)  # update config with task specific params
     if max_source_length is None:
         max_source_length = tokenizer.model_max_length
+    if prefix is None:
+        prefix = prefix or getattr(model.config, "prefix", "") or ""
     ds = Seq2SeqDataset(
         tokenizer,
         data_dir,
@@ -64,7 +69,9 @@ def eval_data_dir(
         max_target_length=1024,
         type_path=type_path,
         n_obs=n_obs,
-        prefix=model.config.prefix,
+        src_lang=src_lang,
+        tgt_lang=tgt_lang,
+        prefix=prefix,
     )
     # I set shuffle=True for a more accurate progress bar.
     # If all the longest samples are first, the prog bar estimate is too high at the beginning.
@@ -118,6 +125,11 @@ def run_generate():
         required=False,
         help="How long should master process wait for other processes to finish.",
     )
+    parser.add_argument("--src_lang", type=str, default=None, required=False)
+    parser.add_argument("--tgt_lang", type=str, default=None, required=False)
+    parser.add_argument(
+        "--prefix", type=str, required=False, default=None, help="will be added to the begininng of src examples"
+    )
     parser.add_argument("--fp16", action="store_true")
     parser.add_argument("--debug", action="store_true")
     start_time = time.time()
@@ -144,6 +156,9 @@ def run_generate():
         local_rank=args.local_rank,
         n_obs=args.n_obs,
         max_source_length=args.max_source_length,
+        prefix=args.prefix,
+        src_lang=args.src_lang,
+        tgt_lang=args.tgt_lang,
         **generate_kwargs,
     )
 

src/transformers/tokenization_mbart.py

@@ -168,6 +168,7 @@ class MBartTokenizer(XLMRobertaTokenizer):
         truncation: bool = True,
         padding: str = "longest",
         return_tensors: str = "pt",
+        add_prefix_space: bool = False,  # ignored
         **kwargs,
     ) -> BatchEncoding:
         """Prepare a batch that can be passed directly to an instance of MBartModel.