dianskip/ai-voice-cloning
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fixes

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mrq 2023-02-21 04:22:11 +00:00
parent bbc2d26289
commit b6f7aa6264
1 changed files with 17 additions and 22 deletions
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37
src/utils.py
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@ -415,7 +415,7 @@ def run_training(config_path, verbose=False, buffer_size=8, progress=gr.Progress
its = config['train']['niter'] its = config['train']['niter']
checkpoint = 0 checkpoint = 0
checkpoints = config['logger']['save_checkpoint_freq'] / its checkpoints = its / config['logger']['save_checkpoint_freq']
buffer_size = 8 buffer_size = 8
open_state = False open_state = False
@ -443,40 +443,35 @@ def run_training(config_path, verbose=False, buffer_size=8, progress=gr.Progress
elif progress is not None: elif progress is not None:
if line.find(' 0%|') == 0: if line.find(' 0%|') == 0:
open_state = True open_state = True
it_time_start = time.time()
elif line.find('100%|') == 0 and open_state: elif line.find('100%|') == 0 and open_state:
it_time_end = time.time()
open_state = False open_state = False
it = it + 1 it = it + 1
it_time_end = time.time()
it_time_delta = it_time_end-it_time_start it_time_delta = it_time_end-it_time_start
it_rate = f'[{"{:.3f}".format(it_time_delta)}s/it]' if it_time_delta >= 1 and it_time_delta != 0 else f'[{"{:.3f}".format(1/it_time_delta)}it/s]' # I doubt anyone will have it/s rates, but its here it_time_start = time.time()
it_rate = f'[{"{:.3f}".format(it_time_delta)}s/it]' if it_time_delta >= 1 else f'[{"{:.3f}".format(1/it_time_delta)}it/s]' # I doubt anyone will have it/s rates, but its here
progress(it / float(its), f'[{it}/{its}] {it_rate} Training... {status}') progress(it / float(its), f'[{it}/{its}] {it_rate} Training... {status}')
# try because I haven't tested this yet if line.find('INFO: [epoch:') >= 0:
try: # easily rip out our stats...
if line.find('INFO: [epoch:') >= 0: match = re.findall(r'\b([a-z_0-9]+?)\b: ([0-9]\.[0-9]+?e[+-]\d+)\b', line)
# easily rip out our stats... if match and len(match) > 0:
match = re.findall(r'\b([a-z_0-9]+?)\b: ([0-9]\.[0-9]+?e[+-]\d+)\b', line) for k, v in match:
if match and len(match) > 0: info[k] = float(v)
for k, v in match:
info[k] = float(v)
# ...and returns our loss rate # ...and returns our loss rate
# it would be nice for losses to be shown at every step # it would be nice for losses to be shown at every step
if 'loss_gpt_total' in info: if 'loss_gpt_total' in info:
status = f"Total loss at step {int(info['step'])}: {info['loss_gpt_total']}" status = f"Total loss at step {int(info['step'])}: {info['loss_gpt_total']}"
except Exception as e: elif line.find('Saving models and training states') >= 0:
pass
if line.find('Saving models and training states') >= 0:
checkpoint = checkpoint + 1 checkpoint = checkpoint + 1
progress(checkpoint / float(checkpoints), f'[{checkpoint}/{checkpoints}] Saving checkpoint...') progress(checkpoint / float(checkpoints), f'[{checkpoint}/{checkpoints}] Saving checkpoint...')
print(f"[Training] [{datetime.now().isoformat()}] {line[:-1]}") print(f"[Training] [{datetime.now().isoformat()}] {line[:-1]}")
if verbose: if verbose or not training_started:
yield "".join(buffer[-buffer_size:]) yield "".join(buffer[-buffer_size:])
training_process.stdout.close() training_process.stdout.close()