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Use Path.stem for simplicity

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oobabooga 2023-04-03 00:54:56 -03:00
parent ea97303509
commit 2a267011dc
2 changed files with 6 additions and 6 deletions
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4
modules/training.py
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@ -20,7 +20,7 @@ MAX_STEPS = 0
CURRENT_GRADIENT_ACCUM = 1 CURRENT_GRADIENT_ACCUM = 1
def get_dataset(path: str, ext: str): def get_dataset(path: str, ext: str):
return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path(path).glob(f'*.{ext}'))), key=str.lower) return ['None'] + sorted(set((k.stem for k in Path(path).glob(f'*.{ext}'))), key=str.lower)
def create_train_interface(): def create_train_interface():
with gr.Tab('Train LoRA', elem_id='lora-train-tab'): with gr.Tab('Train LoRA', elem_id='lora-train-tab'):
@ -104,7 +104,7 @@ def do_train(lora_name: str, micro_batch_size: int, batch_size: int, epochs: int
actual_lr = float(learning_rate) actual_lr = float(learning_rate)
if cutoff_len <= 0 or micro_batch_size <= 0 or batch_size <= 0 or actual_lr <= 0 or lora_rank <= 0 or lora_alpha <= 0: if cutoff_len <= 0 or micro_batch_size <= 0 or batch_size <= 0 or actual_lr <= 0 or lora_rank <= 0 or lora_alpha <= 0:
yield f"Cannot input zeroes." yield "Cannot input zeroes."
return return
gradient_accumulation_steps = batch_size // micro_batch_size gradient_accumulation_steps = batch_size // micro_batch_size

8
server.py
View File

@ -36,12 +36,12 @@ def get_available_models():
return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower) return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
def get_available_presets(): def get_available_presets():
return sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('presets').glob('*.txt'))), key=str.lower) return sorted(set((k.stem for k in Path('presets').glob('*.txt'))), key=str.lower)
def get_available_prompts(): def get_available_prompts():
prompts = [] prompts = []
prompts += sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('prompts').glob('[0-9]*.txt'))), key=str.lower, reverse=True) prompts += sorted(set((k.stem for k in Path('prompts').glob('[0-9]*.txt'))), key=str.lower, reverse=True)
prompts += sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('prompts').glob('*.txt'))), key=str.lower) prompts += sorted(set((k.stem for k in Path('prompts').glob('*.txt'))), key=str.lower)
prompts += ['None'] prompts += ['None']
return prompts return prompts
@ -53,7 +53,7 @@ def get_available_extensions():
return sorted(set(map(lambda x : x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower) return sorted(set(map(lambda x : x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower)
def get_available_softprompts(): def get_available_softprompts():
return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('softprompts').glob('*.zip'))), key=str.lower) return ['None'] + sorted(set((k.stem for k in Path('softprompts').glob('*.zip'))), key=str.lower)
def get_available_loras(): def get_available_loras():
return ['None'] + sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower) return ['None'] + sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)