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Merged
yqzhishen merged 6 commits into from
Mar 3, 2023
Merged

Optimize tensorboard logging #63

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4982d3c
Save gt wav only once to reduce log size
yqzhishen Mar 3, 2023
b96c662
Change name
yqzhishen Mar 3, 2023
3f272d9
Add mel difference to plot
yqzhishen Mar 3, 2023
899d5d7
Fix color
yqzhishen Mar 3, 2023
02587e0
Change plot size
yqzhishen Mar 3, 2023
fa55526
Tight layout
yqzhishen Mar 3, 2023
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6 changes: 3 additions & 3 deletions src/diffsinger_task.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -93,7 +93,7 @@ def validation_step(self, sample, batch_idx):
else:
gt_f0 = denorm_f0(sample['f0'], sample['uv'], hparams)
pred_f0 = model_out.get('f0_denorm')
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], is_mel=True, gt_f0=gt_f0, f0=pred_f0)
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], gt_f0=gt_f0, pred_f0=pred_f0)
self.plot_mel(batch_idx, sample['mels'], model_out['mel_out'], name=f'diffmel_{batch_idx}')
self.plot_mel(batch_idx, sample['mels'], model_out['fs2_mel'], name=f'fs2mel_{batch_idx}')
return outputs
Expand DownExpand Up@@ -200,7 +200,7 @@ def validation_step(self, sample, batch_idx):
else:
gt_f0 = denorm_f0(sample['f0'], sample['uv'], hparams)
pred_f0 = model_out.get('f0_denorm')
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], is_mel=True, gt_f0=gt_f0, f0=pred_f0)
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], gt_f0=gt_f0, pred_f0=pred_f0)
self.plot_mel(batch_idx, sample['mels'], model_out['mel_out'], name=f'diffmel_{batch_idx}')
self.plot_mel(batch_idx, sample['mels'], fs2_mel, name=f'fs2mel_{batch_idx}')
return outputs
Expand DownExpand Up@@ -341,7 +341,7 @@ def validation_step(self, sample, batch_idx):
else:
gt_f0 = denorm_f0(sample['f0'], sample['uv'], hparams)
pred_f0 = model_out.get('f0_denorm')
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], is_mel=True, gt_f0=gt_f0, f0=pred_f0)
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], gt_f0=gt_f0, pred_f0=pred_f0)
self.plot_mel(batch_idx, sample['mels'], model_out['mel_out'], name=f'diffmel_{batch_idx}')
#self.plot_mel(batch_idx, sample['mels'], model_out['fs2_mel'], name=f'fs2mel_{batch_idx}')
if hparams['use_pitch_embed']:
Expand Down
24 changes: 13 additions & 11 deletions src/diffspeech_task.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@ def __init__(self):
super(DiffSpeechTask, self).__init__()
self.dataset_cls = FastSpeechDataset
self.vocoder: BaseVocoder = get_vocoder_cls(hparams)()
self.logged_gt_wav = set()

def build_tts_model(self):
mel_bins = hparams['audio_num_mel_bins']
Expand DownExpand Up@@ -102,21 +103,22 @@ def validation_step(self, sample, batch_idx):
model_out = self.model(
txt_tokens, spk_embed=spk_embed, mel2ph=mel2ph, f0=f0, uv=uv, energy=energy, ref_mels=None, infer=True)
gt_f0 = denorm_f0(sample['f0'], sample['uv'], hparams)
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], is_mel=True, gt_f0=gt_f0, f0=model_out.get('f0_denorm'))
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], gt_f0=gt_f0,
pred_f0=model_out.get('f0_denorm'))
self.plot_mel(batch_idx, sample['mels'], model_out['mel_out'])
return outputs

############
# validation plots
############
def plot_wav(self, batch_idx, gt_wav, wav_out, is_mel=False, gt_f0=None, f0=None, name=None):
gt_wav = gt_wav[0].cpu().numpy()
wav_out = wav_out[0].cpu().numpy()
def plot_wav(self, batch_idx, gt_mel, pred_mel, gt_f0=None, pred_f0=None):
gt_mel = gt_mel[0].cpu().numpy()
pred_mel = pred_mel[0].cpu().numpy()
gt_f0 = gt_f0[0].cpu().numpy()
f0 = f0[0].cpu().numpy()
if is_mel:
gt_wav = self.vocoder.spec2wav(gt_wav, f0=gt_f0)
wav_out = self.vocoder.spec2wav(wav_out, f0=f0)
self.logger.experiment.add_audio(f'gt_{batch_idx}', gt_wav, sample_rate=hparams['audio_sample_rate'], global_step=self.global_step)
self.logger.experiment.add_audio(f'wav_{batch_idx}', wav_out, sample_rate=hparams['audio_sample_rate'], global_step=self.global_step)

pred_f0 = pred_f0[0].cpu().numpy()
if batch_idx not in self.logged_gt_wav:
gt_wav = self.vocoder.spec2wav(gt_mel, f0=gt_f0)
self.logger.experiment.add_audio(f'gt_{batch_idx}', gt_wav, sample_rate=hparams['audio_sample_rate'], global_step=self.global_step)
self.logged_gt_wav.add(batch_idx)
pred_wav = self.vocoder.spec2wav(pred_mel, f0=pred_f0)
self.logger.experiment.add_audio(f'pred_{batch_idx}', pred_wav, sample_rate=hparams['audio_sample_rate'], global_step=self.global_step)
2 changes: 1 addition & 1 deletion src/naive_task.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -82,7 +82,7 @@ def validation_step(self, sample, batch_idx):
else:
gt_f0 = denorm_f0(sample['f0'], sample['uv'], hparams)
pred_f0 = gt_f0
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], is_mel=True, gt_f0=gt_f0, f0=pred_f0)
self.plot_wav(batch_idx, sample['mels'], model_out['mel_out'], gt_f0=gt_f0, pred_f0=pred_f0)
self.plot_mel(batch_idx, sample['mels'], model_out['mel_out'], name=f'diffmel_{batch_idx}')

return outputs
2 changes: 1 addition & 1 deletion src/vocoders/base_vocoder.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -20,7 +20,7 @@ def get_vocoder_cls(hparams):


class BaseVocoder:
def spec2wav(self, mel):
def spec2wav(self, mel, **kwargs):
"""

:param mel: [T, 80]
Expand Down
2 changes: 1 addition & 1 deletion tts/tasks/fs2.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -285,10 +285,10 @@ def add_energy_loss(self, energy_pred, energy, losses):
# validation plots
############
def plot_mel(self, batch_idx, spec, spec_out, name=None):
spec_cat = torch.cat([spec, spec_out], -1)
name = f'mel_{batch_idx}' if name is None else name
vmin = hparams['mel_vmin']
vmax = hparams['mel_vmax']
spec_cat = torch.cat([(spec_out - spec).abs() + vmin, spec, spec_out], -1)
self.logger.experiment.add_figure(name, spec_to_figure(spec_cat[0], vmin, vmax), self.global_step)

def plot_dur(self, batch_idx, sample, model_out):
Expand Down
3 changes: 2 additions & 1 deletion utils/plot.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,9 @@
def spec_to_figure(spec, vmin=None, vmax=None):
if isinstance(spec, torch.Tensor):
spec = spec.cpu().numpy()
fig = plt.figure(figsize=(12, 6))
fig = plt.figure(figsize=(12, 9))
plt.pcolor(spec.T, vmin=vmin, vmax=vmax)
plt.tight_layout()
return fig


Expand Down