dianskip/ai-voice-cloning
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i hate gradio I hate having to specify step=1

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mrq 2023-02-19 17:12:39 +00:00
parent 4f79b3724b
commit ec76676b16
1 changed files with 2 additions and 1 deletions
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src/webui.py
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@ -196,6 +196,7 @@ def save_training_settings_proxy( iterations, batch_size, learning_rate, learnin
batch_size = lines batch_size = lines
messages.append(f"Batch size is larger than your dataset, clamping batch size to: {batch_size}") messages.append(f"Batch size is larger than your dataset, clamping batch size to: {batch_size}")
if batch_size / mega_batch_factor < 2: if batch_size / mega_batch_factor < 2:
mega_batch_factor = int(batch_size / 2) mega_batch_factor = int(batch_size / 2)
messages.append(f"Mega batch factor is too large for the given batch size, clamping mega batch factor to: {mega_batch_factor}") messages.append(f"Mega batch factor is too large for the given batch size, clamping mega batch factor to: {mega_batch_factor}")
@ -358,7 +359,7 @@ def setup_gradio():
gr.Slider(label="Batch Size", minimum=2, maximum=128, value=64), gr.Slider(label="Batch Size", minimum=2, maximum=128, value=64),
gr.Slider(label="Learning Rate", value=1e-5, minimum=0, maximum=1e-4, step=1e-6), gr.Slider(label="Learning Rate", value=1e-5, minimum=0, maximum=1e-4, step=1e-6),
gr.Textbox(label="Learning Rate Schedule", placeholder="[ 200, 300, 400, 500 ]"), gr.Textbox(label="Learning Rate Schedule", placeholder="[ 200, 300, 400, 500 ]"),
gr.Slider(label="Mega Batch Factor", minimum=1, maximum=16, value=4), gr.Slider(label="Mega Batch Factor", minimum=1, maximum=16, value=4, step=1),
gr.Number(label="Print Frequency", value=50), gr.Number(label="Print Frequency", value=50),
gr.Number(label="Save Frequency", value=50), gr.Number(label="Save Frequency", value=50),
gr.Textbox(label="Resume State Path", placeholder="./training/${voice}-finetune/training_state/${last_state}.state"), gr.Textbox(label="Resume State Path", placeholder="./training/${voice}-finetune/training_state/${last_state}.state"),