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Use Path.stem for simplicity

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This commit is contained in:
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
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():
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)
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
gradient_accumulation_steps = batch_size // micro_batch_size