keep_training #118
|
@ -752,8 +752,8 @@ class TrainingState():
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|||
|
||||
models = sorted([ int(d[:-8]) for d in os.listdir(f'{self.dataset_dir}/models/') if d[-8:] == "_gpt.pth" ])
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states = sorted([ int(d[:-6]) for d in os.listdir(f'{self.dataset_dir}/training_state/') if d[-6:] == ".state" ])
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remove_models = models[:-2]
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remove_states = states[:-2]
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remove_models = models[:-keep]
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remove_states = states[:-keep]
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for d in remove_models:
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path = f'{self.dataset_dir}/models/{d}_gpt.pth'
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|
@ -898,6 +898,9 @@ class TrainingState():
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if should_return:
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result = "".join(self.buffer) if not self.training_started else message
|
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|
||||
if keep_x_past_checkpoints > 0:
|
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self.cleanup_old(keep=keep_x_past_checkpoints)
|
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|
||||
return (
|
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result,
|
||||
percent,
|
||||
|
|
|
@ -497,7 +497,7 @@ def setup_gradio():
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training_output = gr.TextArea(label="Console Output", interactive=False, max_lines=8)
|
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verbose_training = gr.Checkbox(label="Verbose Console Output", value=True)
|
||||
|
||||
training_keep_x_past_datasets = gr.Slider(label="Keep X Previous States", minimum=0, maximum=8, value=0, step=1)
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keep_x_past_checkpoints = gr.Slider(label="Keep X Previous States", minimum=0, maximum=8, value=0, step=1)
|
||||
with gr.Row():
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||||
start_training_button = gr.Button(value="Train")
|
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stop_training_button = gr.Button(value="Stop")
|
||||
|
@ -708,7 +708,7 @@ def setup_gradio():
|
|||
inputs=[
|
||||
training_configs,
|
||||
verbose_training,
|
||||
training_keep_x_past_datasets,
|
||||
keep_x_past_checkpoints,
|
||||
],
|
||||
outputs=[
|
||||
training_output,
|
||||
|
|
Loading…
Reference in New Issue
Block a user