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upgrade gradio to 4.21.0

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This commit is contained in:
hiyouga
2024-03-30 20:37:08 +08:00
parent a0333bb0ce
commit 831c5321ac
18 changed files with 167 additions and 159 deletions
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22
src/llmtuner/webui/components/train.py
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@@ -68,7 +68,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
)
)
with gr.Accordion(label="Extra config", open=False) as extra_tab:
with gr.Accordion(open=False) as extra_tab:
with gr.Row():
logging_steps = gr.Slider(value=5, minimum=5, maximum=1000, step=5)
save_steps = gr.Slider(value=100, minimum=10, maximum=5000, step=10)
@@ -113,7 +113,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
)
)
with gr.Accordion(label="Freeze config", open=False) as freeze_tab:
with gr.Accordion(open=False) as freeze_tab:
with gr.Row():
num_layer_trainable = gr.Slider(value=3, minimum=1, maximum=128, step=1, scale=2)
name_module_trainable = gr.Textbox(value="all", scale=3)
@@ -125,7 +125,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
)
)
with gr.Accordion(label="LoRA config", open=False) as lora_tab:
with gr.Accordion(open=False) as lora_tab:
with gr.Row():
lora_rank = gr.Slider(value=8, minimum=1, maximum=1024, step=1, scale=1)
lora_alpha = gr.Slider(value=16, minimum=1, maximum=2048, step=1, scale=1)
@@ -155,7 +155,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
)
)
with gr.Accordion(label="RLHF config", open=False) as rlhf_tab:
with gr.Accordion(open=False) as rlhf_tab:
with gr.Row():
dpo_beta = gr.Slider(value=0.1, minimum=0, maximum=1, step=0.01, scale=1)
dpo_ftx = gr.Slider(value=0, minimum=0, maximum=10, step=0.01, scale=1)
@@ -163,7 +163,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
training_stage.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False).then(
list_adapters,
[engine.manager.get_elem_by_name("top.model_name"), engine.manager.get_elem_by_name("top.finetuning_type")],
[engine.manager.get_elem_by_id("top.model_name"), engine.manager.get_elem_by_id("top.finetuning_type")],
[reward_model],
queue=False,
).then(autoset_packing, [training_stage], [packing], queue=False)
@@ -171,7 +171,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
input_elems.update({dpo_beta, dpo_ftx, reward_model})
elem_dict.update(dict(rlhf_tab=rlhf_tab, dpo_beta=dpo_beta, dpo_ftx=dpo_ftx, reward_model=reward_model))
with gr.Accordion(label="GaLore config", open=False) as galore_tab:
with gr.Accordion(open=False) as galore_tab:
with gr.Row():
use_galore = gr.Checkbox(scale=1)
galore_rank = gr.Slider(value=16, minimum=1, maximum=1024, step=1, scale=2)
@@ -205,7 +205,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
resume_btn = gr.Checkbox(visible=False, interactive=False)
process_bar = gr.Slider(visible=False, interactive=False)
with gr.Box():
with gr.Row():
output_box = gr.Markdown()
with gr.Column(scale=1):
@@ -214,10 +214,10 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
input_elems.add(output_dir)
output_elems = [output_box, process_bar]
cmd_preview_btn.click(engine.runner.preview_train, input_elems, output_elems)
cmd_preview_btn.click(engine.runner.preview_train, input_elems, output_elems, concurrency_limit=None)
start_btn.click(engine.runner.run_train, input_elems, output_elems)
stop_btn.click(engine.runner.set_abort, queue=False)
resume_btn.change(engine.runner.monitor, outputs=output_elems)
resume_btn.change(engine.runner.monitor, outputs=output_elems, concurrency_limit=None)
elem_dict.update(
dict(
@@ -235,8 +235,8 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
output_box.change(
gen_plot,
[
engine.manager.get_elem_by_name("top.model_name"),
engine.manager.get_elem_by_name("top.finetuning_type"),
engine.manager.get_elem_by_id("top.model_name"),
engine.manager.get_elem_by_id("top.finetuning_type"),
output_dir,
],
loss_viewer,