forked from mrq/ai-voice-cloning
actually fixed the training output text parser
This commit is contained in:
parent
65329dba31
commit
aafeb9f96a
70
src/utils.py
70
src/utils.py
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@ -470,10 +470,14 @@ class TrainingState():
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self.epoch_rate = ""
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self.epoch_time_start = 0
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self.epoch_time_end = 0
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self.epoch_time_deltas = 0
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self.epoch_taken = 0
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self.it_rate = ""
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self.it_time_start = 0
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self.it_time_end = 0
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self.it_time_deltas = 0
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self.it_taken = 0
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self.last_step = 0
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self.eta = "?"
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@ -482,8 +486,7 @@ class TrainingState():
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print("Spawning process: ", " ".join(self.cmd))
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self.process = subprocess.Popen(self.cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, universal_newlines=True)
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def parse(self, line, verbose=False, buffer_size=8, progress=None, owner=True):
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if owner:
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def parse(self, line, verbose=False, buffer_size=8, progress=None ):
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self.buffer.append(f'{line}')
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# rip out iteration info
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@ -499,10 +502,10 @@ class TrainingState():
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if match and len(match) > 0:
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self.it = int(match[0].replace(",", ""))
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else:
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lapsed = line.find('100%|') == 0 and self.open_state
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lapsed = False
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if line.find('%|') > 0:
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match = re.findall(r' +?(\d+)%\|(.+?)\| (\d+|\?)\/(\d+|\?) \[(.+?)<(.+?), +(.+?)\]', line)
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match = re.findall(r'(\d+)%\|(.+?)\| (\d+|\?)\/(\d+|\?) \[(.+?)<(.+?), +(.+?)\]', line)
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if match and len(match) > 0:
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match = match[0]
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percent = int(match[0])/100.0
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@ -513,38 +516,48 @@ class TrainingState():
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until = match[5]
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rate = match[6]
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epoch_percent = self.epoch / float(self.epochs)
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epoch_percent = self.it / float(self.its) # self.epoch / float(self.epochs)
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if owner:
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last_step = self.last_step
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self.last_step = step
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if last_step < step:
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self.it = self.it + (step - last_step)
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if last_step > step and step == 0:
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if last_step == step and step == steps:
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lapsed = True
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self.it_time_end = time.time()
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self.it_time_delta = self.it_time_end-self.it_time_start
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self.it_time_start = time.time()
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self.it_rate = f'[{"{:.3f}".format(self.it_time_delta)}s/it]' if self.it_time_delta >= 1 else f'[{"{:.3f}".format(1/self.it_time_delta)}it/s]'
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try:
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rate = f'[{"{:.3f}".format(self.it_time_delta)}s/it]' if self.it_time_delta >= 1 else f'[{"{:.3f}".format(1/self.it_time_delta)}it/s]'
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self.it_rate = rate
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except Exception as e:
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pass
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self.eta = (self.its - self.it) * self.it_time_delta
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self.eta_hhmmss = str(timedelta(seconds=int(self.eta)))
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"""
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# I wanted frequently updated ETA, but I can't wrap my noggin around getting it to work on an empty belly
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# will fix later
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#self.eta = (self.its - self.it) * self.it_time_delta
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self.it_time_deltas = self.it_time_deltas + self.it_time_delta
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self.it_taken = self.it_taken + 1
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self.eta = (self.its - self.it) * (self.it_time_deltas / self.it_taken)
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try:
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eta = str(timedelta(seconds=int(self.eta)))
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self.eta_hhmmss = eta
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except Exception as e:
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pass
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"""
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message = f'[{self.epoch}/{self.epochs}] [{self.it}/{self.its}] [ETA: {self.eta_hhmmss}] {self.epoch_rate} / {self.it_rate} {self.status}'
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if progress is not None:
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progress(epoch_percent, message)
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if owner:
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# print(f'{"{:.3f}".format(percent*100)}% {message}')
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self.buffer.append(f'[{"{:.3f}".format(epoch_percent*100)}% / {"{:.3f}".format(percent*100)}%] {message}')
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if line.find('%|') > 0 and not self.open_state:
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if owner:
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self.open_state = True
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elif lapsed and self.open_state:
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if owner:
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self.open_state = False
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if lapsed:
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self.epoch = self.epoch + 1
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self.it = int(self.epoch * (self.dataset_size / self.batch_size))
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@ -552,8 +565,16 @@ class TrainingState():
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self.epoch_time_delta = self.epoch_time_end-self.epoch_time_start
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self.epoch_time_start = time.time()
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self.epoch_rate = f'[{"{:.3f}".format(self.epoch_time_delta)}s/epoch]' if self.epoch_time_delta >= 1 else f'[{"{:.3f}".format(1/self.epoch_time_delta)}epoch/s]' # I doubt anyone will have it/s rates, but its here
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self.eta = (self.epochs - self.epoch) * self.epoch_time_delta
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self.eta_hhmmss = str(timedelta(seconds=int(self.eta)))
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#self.eta = (self.epochs - self.epoch) * self.epoch_time_delta
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self.epoch_time_deltas = self.epoch_time_deltas + self.epoch_time_delta
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self.epoch_taken = self.epoch_taken + 1
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self.eta = (self.epochs - self.epoch) * (self.epoch_time_deltas / self.epoch_taken)
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try:
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eta = str(timedelta(seconds=int(self.eta)))
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self.eta_hhmmss = eta
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except Exception as e:
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pass
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percent = self.epoch / float(self.epochs)
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message = f'[{self.epoch}/{self.epochs}] [{self.it}/{self.its}] [ETA: {self.eta_hhmmss}] {self.epoch_rate} / {self.it_rate} {self.status}'
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@ -561,12 +582,10 @@ class TrainingState():
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if progress is not None:
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progress(percent, message)
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if owner:
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print(f'{"{:.3f}".format(percent*100)}% {message}')
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self.buffer.append(f'{"{:.3f}".format(percent*100)}% {message}')
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if line.find('INFO: [epoch:') >= 0:
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if owner:
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# easily rip out our stats...
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match = re.findall(r'\b([a-z_0-9]+?)\b: ([0-9]\.[0-9]+?e[+-]\d+)\b', line)
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if match and len(match) > 0:
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@ -578,17 +597,16 @@ class TrainingState():
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print(self.status)
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self.buffer.append(self.status)
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elif line.find('Saving models and training states') >= 0:
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if owner:
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self.checkpoint = self.checkpoint + 1
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percent = self.checkpoint / float(self.checkpoints)
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message = f'[{self.checkpoint}/{self.checkpoints}] Saving checkpoint...'
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if progress is not None:
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progress(percent, message)
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if owner:
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print(f'{"{:.3f}".format(percent*100)}% {message}')
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self.buffer.append(f'{"{:.3f}".format(percent*100)}% {message}')
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if owner:
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self.buffer = self.buffer[-buffer_size:]
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if verbose or not self.training_started:
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return "".join(self.buffer)
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@ -609,7 +627,7 @@ def run_training(config_path, verbose=False, buffer_size=8, progress=gr.Progress
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for line in iter(training_state.process.stdout.readline, ""):
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res = training_state.parse( line=line, verbose=verbose, buffer_size=buffer_size, progress=progress, owner=True )
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res = training_state.parse( line=line, verbose=verbose, buffer_size=buffer_size, progress=progress )
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print(f"[Training] [{datetime.now().isoformat()}] {line[:-1]}")
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if res:
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yield res
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@ -628,7 +646,7 @@ def reconnect_training(verbose=False, buffer_size=8, progress=gr.Progress(track_
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return "Training not in progress"
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for line in iter(training_state.process.stdout.readline, ""):
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res = training_state.parse( line=line, verbose=verbose, buffer_size=buffer_size, progress=progress, owner=True )
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res = training_state.parse( line=line, verbose=verbose, buffer_size=buffer_size, progress=progress )
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if res:
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yield res
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