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Add evaluation logic for gpt_asr_hf2

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James Betker 2021-12-02 21:04:36 -07:00
parent 47fe032a3d
commit 04454ee63a
2 changed files with 10 additions and 9 deletions
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17
codes/models/gpt_voice/gpt_asr_hf2.py
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@ -45,7 +45,9 @@ class MelEncoder(nn.Module):
) )
def forward(self, x): def forward(self, x):
return self.encoder(x) for e in self.encoder:
x = e(x)
return x
class GPT2InferenceModel(GPT2PreTrainedModel): class GPT2InferenceModel(GPT2PreTrainedModel):
@ -262,22 +264,21 @@ class GptAsrHf2(nn.Module):
mel_emb = self.mel_encoder(mel_inputs) mel_emb = self.mel_encoder(mel_inputs)
assert mel_emb.shape[-1] <= self.max_mel_frames assert mel_emb.shape[-1] <= self.max_mel_frames
mel_emb = F.pad(mel_emb, (0, self.max_mel_frames - mel_emb.shape[-1]))
mel_emb = mel_emb.permute(0,2,1).contiguous() mel_emb = mel_emb.permute(0,2,1).contiguous()
mel_emb = mel_emb + self.mel_pos_embedding(torch.arange(mel_emb.shape[1], device=mel_emb.device)) mel_emb = mel_emb + self.mel_pos_embedding(torch.arange(mel_emb.shape[1], device=mel_emb.device))
self.inference_model.store_mel_emb(mel_emb) self.inference_model.store_mel_emb(mel_emb)
# "fake_inputs" are stand-ins for the MEL frames, which will be injected with the prep_inputs function above. # "fake_inputs" are stand-ins for the MEL frames, which will be injected with the prep_inputs function above.
if cond_text is None: if cond_text is None:
fake_inputs = torch.full((mel_inputs.shape[0],self.max_mel_frames+1,), fill_value=1, dtype=torch.long, device=mel_inputs.device) fake_inputs = torch.full((mel_emb.shape[0],mel_emb.shape[1]+1,), fill_value=1, dtype=torch.long, device=mel_inputs.device)
fake_inputs[:,-1] = self.NUMBER_SYMBOLS fake_inputs[:,-1] = self.START_TOKEN
else: else:
cond_used = 10 cond_used = 10
fake_inputs = torch.full((mel_inputs.shape[0],self.max_mel_frames+1+cond_used,), fill_value=1, dtype=torch.long, device=mel_inputs.device) fake_inputs = torch.full((mel_emb.shape[0],mel_emb.shape[1]+1+cond_used,), fill_value=1, dtype=torch.long, device=mel_inputs.device)
fake_inputs[:,-1-cond_used] = self.NUMBER_SYMBOLS fake_inputs[:,-1-cond_used] = self.START_TOKEN
fake_inputs[:, -cond_used:] = cond_text[:, :cond_used] fake_inputs[:, -cond_used:] = cond_text[:, :cond_used]
gen = self.inference_model.generate(fake_inputs, do_sample=do_sample, bos_token_id=self.NUMBER_SYMBOLS, pad_token_id=0, eos_token_id=0, gen = self.inference_model.generate(fake_inputs, do_sample=do_sample, bos_token_id=self.START_TOKEN, pad_token_id=0, eos_token_id=0,
max_length=self.max_symbols_per_phrase+self.max_mel_frames, temperature=temperature, num_beams=num_beams, use_cache=True) max_length=self.max_symbols_per_phrase+mel_emb.shape[1], temperature=temperature, num_beams=num_beams, use_cache=True)
return gen[:, self.max_mel_frames:] return gen[:, self.max_mel_frames:]

2
codes/scripts/audio/asr_eval.py
View File

@ -44,7 +44,7 @@ if __name__ == "__main__":
torch.backends.cudnn.benchmark = True torch.backends.cudnn.benchmark = True
want_metrics = False want_metrics = False
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('-opt', type=str, help='Path to options YAML file.', default='../options/test_gpt_asr_hf.yml') parser.add_argument('-opt', type=str, help='Path to options YAML file.', default='../options/test_gpt_asr_hf2.yml')
opt = option.parse(parser.parse_args().opt, is_train=False) opt = option.parse(parser.parse_args().opt, is_train=False)
opt = option.dict_to_nonedict(opt) opt = option.dict_to_nonedict(opt)
utils.util.loaded_options = opt utils.util.loaded_options = opt