54 lines
2.3 KiB
Python
54 lines
2.3 KiB
Python
# coding=utf-8
|
|
# Copyright 2020 Marian Team Authors and The HuggingFace Inc. team.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""PyTorch MarianMTModel model, ported from the Marian C++ repo."""
|
|
|
|
|
|
from .configuration_marian import MarianConfig
|
|
from .modeling_bart import BartForConditionalGeneration
|
|
|
|
|
|
# See all Marian models at https://huggingface.co/models?search=Helsinki-NLP
|
|
|
|
|
|
class MarianMTModel(BartForConditionalGeneration):
|
|
config_class = MarianConfig
|
|
r"""
|
|
Pytorch version of marian-nmt's transformer.h (c++). Designed for the OPUS-NMT translation checkpoints.
|
|
Model API is identical to BartForConditionalGeneration.
|
|
Available models are listed at `Model List <https://huggingface.co/models?search=Helsinki-NLP>`__
|
|
|
|
Examples::
|
|
|
|
>>> from transformers import MarianTokenizer, MarianMTModel
|
|
>>> from typing import List
|
|
>>> src = 'fr' # source language
|
|
>>> trg = 'en' # target language
|
|
>>> sample_text = "où est l'arrêt de bus ?"
|
|
>>> mname = f'Helsinki-NLP/opus-mt-{src}-{trg}'
|
|
|
|
>>> model = MarianMTModel.from_pretrained(mname)
|
|
>>> tok = MarianTokenizer.from_pretrained(mname)
|
|
>>> batch = tok.prepare_seq2seq_batch(src_texts=[sample_text]) # don't need tgt_text for inference
|
|
>>> gen = model.generate(**batch) # for forward pass: model(**batch)
|
|
>>> words: List[str] = tok.batch_decode(gen, skip_special_tokens=True) # returns "Where is the bus stop ?"
|
|
|
|
"""
|
|
|
|
def adjust_logits_during_generation(self, logits, cur_len, max_length):
|
|
logits[:, self.config.pad_token_id] = float("-inf") # never predict pad token.
|
|
if cur_len == max_length - 1 and self.config.eos_token_id is not None:
|
|
self._force_token_ids_generation(logits, self.config.eos_token_id)
|
|
return logits
|