pass langs parameter to certain XLM models (#2734)

* pass langs parameter to certain XLM models

Adding an argument that specifies the language the SQuAD dataset is in so language-sensitive XLMs (e.g. `xlm-mlm-tlm-xnli15-1024`) don't default to language `0`.
Allows resolution of issue #1799 .

* fixing from `make style`

* fixing style (again)
This commit is contained in:
Yuval Pinter 2020-02-04 17:12:42 -05:00 committed by GitHub
parent 9e5b549b4d
commit d1ab1fab1b
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23

View File

@ -219,6 +219,11 @@ def train(args, train_dataset, model, tokenizer):
inputs.update({"cls_index": batch[5], "p_mask": batch[6]})
if args.version_2_with_negative:
inputs.update({"is_impossible": batch[7]})
if hasattr(model, "config") and hasattr(model.config, "lang2id"):
inputs.update(
{"langs": (torch.ones(batch[0].shape, dtype=torch.int64) * args.lang_id).to(args.device)}
)
outputs = model(**inputs)
# model outputs are always tuple in transformers (see doc)
loss = outputs[0]
@ -330,6 +335,11 @@ def evaluate(args, model, tokenizer, prefix=""):
# XLNet and XLM use more arguments for their predictions
if args.model_type in ["xlnet", "xlm"]:
inputs.update({"cls_index": batch[4], "p_mask": batch[5]})
# for lang_id-sensitive xlm models
if hasattr(model, "config") and hasattr(model.config, "lang2id"):
inputs.update(
{"langs": (torch.ones(batch[0].shape, dtype=torch.int64) * args.lang_id).to(args.device)}
)
outputs = model(**inputs)
@ -635,6 +645,12 @@ def main():
help="If true, all of the warnings related to data processing will be printed. "
"A number of warnings are expected for a normal SQuAD evaluation.",
)
parser.add_argument(
"--lang_id",
default=0,
type=int,
help="language id of input for language-specific xlm models (see tokenization_xlm.PRETRAINED_INIT_CONFIGURATION)",
)
parser.add_argument("--logging_steps", type=int, default=500, help="Log every X updates steps.")
parser.add_argument("--save_steps", type=int, default=500, help="Save checkpoint every X updates steps.")