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evaluation/validation passes language ID during training (oops)

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mrq 2023-10-29 12:00:40 -05:00
parent ed54f4ebec
commit 0aa2a3cc07
2 changed files with 7 additions and 5 deletions
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2
vall_e/data.py
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@ -224,7 +224,7 @@ class Dataset(_Dataset):
self.spkrs_by_spkr_group[spkr_group].append( spkr ) self.spkrs_by_spkr_group[spkr_group].append( spkr )
self.spkr_groups = list(self.spkrs_by_spkr_group.keys()) self.spkr_groups = list(self.spkrs_by_spkr_group.keys())
self.spkr_samplers = { name: Sampler( [*set(speakers)], keep_all=True ) for name, speakers in self.spkrs_by_spkr_group.items() } self.spkr_samplers = { name: Sampler( [*set(speakers)], keep_all=True ) for name, speakers in self.spkrs_by_spkr_group.items() }
if self.sampler_type == "path": if self.sampler_type == "path":

10
vall_e/train.py
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@ -103,9 +103,9 @@ def run_eval(engines, eval_name, dl):
if AR is not None and NAR is not None: if AR is not None and NAR is not None:
name = "+".join(names) name = "+".join(names)
resps_list = AR(text_list=batch["text"], proms_list=batch["proms"], max_steps=cfg.evaluation.steps, sampling_temperature=cfg.evaluation.ar_temperature) resps_list = AR(text_list=batch["text"], proms_list=batch["proms"], lang_list=batch["lang"], max_steps=cfg.evaluation.steps, sampling_temperature=cfg.evaluation.ar_temperature)
resps_list = [ r.unsqueeze(-1) for r in resps_list ] resps_list = [ r.unsqueeze(-1) for r in resps_list ]
resps_list = NAR(text_list=batch["text"], proms_list=batch["proms"], resps_list=resps_list, sampling_temperature=cfg.evaluation.nar_temperature) resps_list = NAR(text_list=batch["text"], proms_list=batch["proms"], lang_list=batch["lang"], resps_list=resps_list, sampling_temperature=cfg.evaluation.nar_temperature)
process( name, batch, resps_list ) process( name, batch, resps_list )
else: else:
@ -113,13 +113,14 @@ def run_eval(engines, eval_name, dl):
model = engines[name] model = engines[name]
if name.startswith("ar+nar"): if name.startswith("ar+nar"):
resps_list = AR_NAR(text_list=batch["text"], proms_list=batch["proms"], max_steps=cfg.evaluation.steps, sampling_temperature=cfg.evaluation.ar_temperature) resps_list = AR_NAR(text_list=batch["text"], proms_list=batch["proms"], lang_list=batch["lang"], max_steps=cfg.evaluation.steps, sampling_temperature=cfg.evaluation.ar_temperature)
resps_list = [ r.unsqueeze(-1) for r in resps_list ] resps_list = [ r.unsqueeze(-1) for r in resps_list ]
resps_list = AR_NAR(text_list=batch["text"], proms_list=batch["proms"], resps_list=resps_list, sampling_temperature=cfg.evaluation.nar_temperature) resps_list = AR_NAR(text_list=batch["text"], proms_list=batch["proms"], lang_list=batch["lang"], resps_list=resps_list, sampling_temperature=cfg.evaluation.nar_temperature)
elif name.startswith("ar"): elif name.startswith("ar"):
resps_list = model( resps_list = model(
text_list=batch["text"], text_list=batch["text"],
proms_list=batch["proms"], proms_list=batch["proms"],
lang_list=batch["lang"],
max_steps=cfg.evaluation.steps, max_steps=cfg.evaluation.steps,
sampling_temperature=cfg.evaluation.ar_temperature, sampling_temperature=cfg.evaluation.ar_temperature,
) )
@ -128,6 +129,7 @@ def run_eval(engines, eval_name, dl):
resps_list = model( resps_list = model(
text_list=batch["text"], text_list=batch["text"],
proms_list=batch["proms"], proms_list=batch["proms"],
lang_list=batch["lang"],
resps_list=[r[..., 0].unsqueeze(-1) for r in batch["resps"]], resps_list=[r[..., 0].unsqueeze(-1) for r in batch["resps"]],
sampling_temperature=cfg.evaluation.nar_temperature, sampling_temperature=cfg.evaluation.nar_temperature,
) )