def build_generator(
self,
models,
args,
seq_gen_cls=None,
extra_gen_cls_kwargs=None,
):
if self.data_cfg.prepend_tgt_lang_tag and args.prefix_size != 1:
raise ValueError('Please set "--prefix-size 1" since '
"target language ID token is prepended as BOS.")
lang_token_ids = {
i
for s, i in self.tgt_dict.indices.items()
if SpeechToTextDataset.is_lang_tag(s)
}
if extra_gen_cls_kwargs is None:
extra_gen_cls_kwargs = {
"symbols_to_strip_from_output": lang_token_ids
}
else:
extra_gen_cls_kwargs[
"symbols_to_strip_from_output"] = lang_token_ids
return super().build_generator(
models,
args,
seq_gen_cls=None,
extra_gen_cls_kwargs=extra_gen_cls_kwargs)
def build_dataset_for_inference(self, src_tokens, src_lengths, **kwargs):
assert self.interactive_tgt_lang is not None
return SpeechToTextDataset(
"interactive", False, self.data_cfg, src_tokens, src_lengths,
tgt_texts=([""] * len(src_tokens)),
tgt_langs=([self.interactive_tgt_lang] * len(src_tokens)),
tgt_dict=self.tgt_dict
)
def get_prefix_token(cls, task, lang):
prefix_size = int(task.data_cfg.prepend_tgt_lang_tag)
prefix_tokens = None
if prefix_size > 0:
assert lang is not None
lang_tag = SpeechToTextDataset.get_lang_tag_idx(
lang, task.tgt_dict)
prefix_tokens = torch.Tensor([lang_tag]).long().unsqueeze(0)
return prefix_tokens
def build_generator(
self,
models,
args,
seq_gen_cls=None,
extra_gen_cls_kwargs=None,
):
if self.data_cfg.prepend_tgt_lang_tag and args.prefix_size != 1:
raise ValueError(
'Please set "--prefix-size 1" since '
"target language ID token is prepended as BOS."
)
lang_token_ids = {
i
for s, i in self.tgt_dict.indices.items()
if SpeechToTextDataset.is_lang_tag(s)
}
if extra_gen_cls_kwargs is None:
extra_gen_cls_kwargs = {}
extra_gen_cls_kwargs["symbols_to_strip_from_output"] = lang_token_ids
eos_token = (
args.eos_token
if "eos_token" in args and args.eos_token is not None
else self.data_cfg.config.get("eos_token", None)
)
if self.data_cfg.prepend_bos_and_append_tgt_lang_tag and not eos_token:
raise Warning(
"Please provide --eos_token to replace eos in sequence generator"
)
eos_id = self.tgt_dict.index(eos_token) if eos_token else None
extra_gen_cls_kwargs["eos"] = eos_id
return super().build_generator(
models, args, seq_gen_cls=None, extra_gen_cls_kwargs=extra_gen_cls_kwargs
)
def build_dataset_for_inference(cls, audio_paths, n_frames):
return SpeechToTextDataset("interactive", False, {}, audio_paths,
n_frames)
def build_dataset_for_inference(self, src_tokens, src_lengths, **kwargs):
return SpeechToTextDataset(
"interactive", False, self.data_cfg, src_tokens, src_lengths
)