From cb273b84281548b1a81b1f149d2a6dfe9782a16e Mon Sep 17 00:00:00 2001
From: mrq <barry.quiggles@protonmail.com>
Date: Thu, 9 Mar 2023 18:34:52 +0000
Subject: [PATCH] cleanup
---
src/utils.py | 47 +++++++++++++++++++++++++++--------------------
src/webui.py | 23 ++++++++++++++++++++---
2 files changed, 47 insertions(+), 23 deletions(-)
diff --git a/src/utils.py b/src/utils.py
index 82ea25b..191e677 100755
--- a/src/utils.py
+++ b/src/utils.py
@@ -1274,6 +1274,15 @@ def optimize_training_settings( **kwargs ):
if vram > (k-1):
return v
return 1
+
+ if settings['gpus'] > get_device_count():
+ settings['gpus'] = get_device_count()
+ messages.append(f"GPU count exceeds defacto GPU count, clamping to: {settings['gpus']}")
+
+ if settings['gpus'] <= 1:
+ settings['gpus'] = 1
+ else:
+ messages.append(f"! EXPERIMENTAL ! Multi-GPU training is extremely particular, expect issues.")
# assuming you have equal GPUs
vram = get_device_vram() * settings['gpus']
@@ -1303,14 +1312,14 @@ def optimize_training_settings( **kwargs ):
messages.append("Resume path specified, but does not exist. Disabling...")
if settings['bitsandbytes']:
- messages.append("BitsAndBytes requested. Please note this is ! EXPERIMENTAL !")
+ messages.append("! EXPERIMENTAL ! BitsAndBytes requested.")
if settings['half_p']:
if settings['bitsandbytes']:
settings['half_p'] = False
messages.append("Half Precision requested, but BitsAndBytes is also requested. Due to redundancies, disabling half precision...")
else:
- messages.append("Half Precision requested. Please note this is ! EXPERIMENTAL !")
+ messages.append("! EXPERIMENTAL ! Half Precision requested.")
if not os.path.exists(get_halfp_model_path()):
convert_to_halfp()
@@ -1343,12 +1352,21 @@ def save_training_settings( **kwargs ):
settings['iterations'] = calc_iterations(epochs=settings['epochs'], lines=lines, batch_size=settings['batch_size'])
messages.append(f"For {settings['epochs']} epochs with {lines} lines, iterating for {settings['iterations']} steps")
- iterations_per_epoch = int(settings['iterations'] / settings['epochs'])
+ iterations_per_epoch = settings['iterations'] / settings['epochs']
settings['print_rate'] = int(settings['print_rate'] * iterations_per_epoch)
settings['save_rate'] = int(settings['save_rate'] * iterations_per_epoch)
settings['validation_rate'] = int(settings['validation_rate'] * iterations_per_epoch)
+ iterations_per_epoch = int(iterations_per_epoch)
+
+ if settings['print_rate'] < 1:
+ settings['print_rate'] = 1
+ if settings['save_rate'] < 1:
+ settings['save_rate'] = 1
+ if settings['validation_rate'] < 1:
+ settings['validation_rate'] = 1
+
settings['validation_batch_size'] = int(settings['batch_size'] / settings['gradient_accumulation_size'])
settings['iterations'] = calc_iterations(epochs=settings['epochs'], lines=lines, batch_size=settings['batch_size'])
@@ -1809,9 +1827,7 @@ def save_args_settings():
# super kludgy )`;
def import_generate_settings(file="./config/generate.json"):
- global GENERATE_SETTINGS_ARGS
-
- defaults = {
+ res = {
'text': None,
'delimiter': None,
'emotion': None,
@@ -1836,19 +1852,9 @@ def import_generate_settings(file="./config/generate.json"):
}
settings, _ = read_generate_settings(file, read_latents=False)
-
- res = []
- if GENERATE_SETTINGS_ARGS is not None:
- for k in GENERATE_SETTINGS_ARGS:
- if k not in defaults:
- continue
- res.append(defaults[k] if not settings or k not in settings or not settings[k] is None else settings[k])
- else:
- for k in defaults:
- res.append(defaults[k] if not settings or k not in settings or not settings[k] is None else settings[k])
-
- return tuple(res)
-
+ if settings is not None:
+ res.update(settings)
+ return res
def reset_generation_settings():
with open(f'./config/generate.json', 'w', encoding="utf-8") as f:
@@ -1978,7 +1984,8 @@ def deduce_autoregressive_model(voice=None):
if os.path.isdir(dir):
counts = sorted([ int(d[:-8]) for d in os.listdir(dir) if d[-8:] == "_gpt.pth" ])
names = [ f'{dir}/{d}_gpt.pth' for d in counts ]
- return names[-1]
+ if len(names) > 0:
+ return names[-1]
if args.autoregressive_model != "auto":
return args.autoregressive_model
diff --git a/src/webui.py b/src/webui.py
index 281f3ac..39abcc4 100755
--- a/src/webui.py
+++ b/src/webui.py
@@ -27,6 +27,7 @@ GENERATE_SETTINGS = {}
TRANSCRIBE_SETTINGS = {}
EXEC_SETTINGS = {}
TRAINING_SETTINGS = {}
+GENERATE_SETTINGS_ARGS = []
PRESETS = {
'Ultra Fast': {'num_autoregressive_samples': 16, 'diffusion_iterations': 30, 'cond_free': False},
@@ -144,6 +145,18 @@ def history_view_results( voice ):
gr.Dropdown.update(choices=sorted(files))
)
+def import_generate_settings_proxy( file=None ):
+ global GENERATE_SETTINGS_ARGS
+ settings = import_generate_settings( file )
+
+ res = []
+ for k in GENERATE_SETTINGS_ARGS:
+ res.append(settings[k] if k in settings else None)
+ print(GENERATE_SETTINGS_ARGS)
+ print(settings)
+ print(res)
+ return tuple(res)
+
def compute_latents_proxy(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
compute_latents( voice=voice, voice_latents_chunks=voice_latents_chunks, progress=progress )
return voice
@@ -221,7 +234,10 @@ def import_training_settings_proxy( voice ):
if k not in settings:
continue
output[k] = settings[k]
+
output = list(output.values())
+ print(list(TRAINING_SETTINGS.keys()))
+ print(output)
messages.append(f"Imported training settings: {injson}")
return output[:-1] + ["\n".join(messages)]
@@ -250,7 +266,7 @@ def history_copy_settings( voice, file ):
def setup_gradio():
global args
global ui
-
+
if not args.share:
def noop(function, return_value=None):
def wrapped(*args, **kwargs):
@@ -273,6 +289,7 @@ def setup_gradio():
autoregressive_models = get_autoregressive_models()
dataset_list = get_dataset_list()
+ global GENERATE_SETTINGS_ARGS
GENERATE_SETTINGS_ARGS = list(inspect.signature(generate_proxy).parameters.keys())[:-1]
for i in range(len(GENERATE_SETTINGS_ARGS)):
arg = GENERATE_SETTINGS_ARGS[i]
@@ -639,7 +656,7 @@ def setup_gradio():
)
- copy_button.click(import_generate_settings,
+ copy_button.click(import_generate_settings_proxy,
inputs=audio_in, # JSON elements cannot be used as inputs
outputs=generate_settings
)
@@ -738,7 +755,7 @@ def setup_gradio():
)
if os.path.isfile('./config/generate.json'):
- ui.load(import_generate_settings, inputs=None, outputs=generate_settings)
+ ui.load(import_generate_settings_proxy, inputs=None, outputs=generate_settings)
if args.check_for_updates:
ui.load(check_for_updates)