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support rope scaling, fix #475 #476 #478

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Former-commit-id: 337d5f68b72230e545e7a94ca789187c7a2b7187
This commit is contained in:
hiyouga
2023-08-12 20:46:27 +08:00
parent cde9f3db57
commit fdfb644f0a
12 changed files with 267 additions and 277 deletions
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57
src/llmtuner/webui/components/eval.py
View File

@@ -14,13 +14,13 @@ def create_eval_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict
with gr.Row():
dataset_dir = gr.Textbox(value=DEFAULT_DATA_DIR, scale=2)
dataset = gr.Dropdown(multiselect=True, scale=4)
preview_btn = gr.Button(interactive=False, scale=1)
data_preview_btn = gr.Button(interactive=False, scale=1)
preview_box, preview_count, preview_samples, close_btn = create_preview_box()
dataset_dir.change(list_dataset, [dataset_dir], [dataset])
dataset.change(can_preview, [dataset_dir, dataset], [preview_btn])
preview_btn.click(
dataset.change(can_preview, [dataset_dir, dataset], [data_preview_btn])
data_preview_btn.click(
get_preview,
[dataset_dir, dataset],
[preview_count, preview_samples, preview_box],
@@ -35,6 +35,7 @@ def create_eval_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict
predict = gr.Checkbox(value=True)
with gr.Row():
cmd_preview_btn = gr.Button()
start_btn = gr.Button()
stop_btn = gr.Button()
@@ -44,35 +45,36 @@ def create_eval_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict
with gr.Box():
output_box = gr.Markdown()
start_btn.click(
runner.run_eval,
[
top_elems["lang"],
top_elems["model_name"],
top_elems["checkpoints"],
top_elems["finetuning_type"],
top_elems["quantization_bit"],
top_elems["template"],
top_elems["source_prefix"],
dataset_dir,
dataset,
max_source_length,
max_target_length,
max_samples,
batch_size,
predict
],
[
output_box,
process_bar
]
)
input_list = [
top_elems["lang"],
top_elems["model_name"],
top_elems["checkpoints"],
top_elems["finetuning_type"],
top_elems["quantization_bit"],
top_elems["template"],
top_elems["source_prefix"],
dataset_dir,
dataset,
max_source_length,
max_target_length,
max_samples,
batch_size,
predict
]
output_list = [
output_box,
process_bar
]
cmd_preview_btn.click(runner.preview_eval, input_list, output_list)
start_btn.click(runner.run_eval, input_list, output_list)
stop_btn.click(runner.set_abort, queue=False)
return dict(
dataset_dir=dataset_dir,
dataset=dataset,
preview_btn=preview_btn,
data_preview_btn=data_preview_btn,
preview_count=preview_count,
preview_samples=preview_samples,
close_btn=close_btn,
@@ -81,6 +83,7 @@ def create_eval_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict
max_samples=max_samples,
batch_size=batch_size,
predict=predict,
cmd_preview_btn=cmd_preview_btn,
start_btn=start_btn,
stop_btn=stop_btn,
output_box=output_box

131
src/llmtuner/webui/components/sft.py
View File

@@ -16,13 +16,13 @@ def create_sft_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict[
with gr.Row():
dataset_dir = gr.Textbox(value=DEFAULT_DATA_DIR, scale=2)
dataset = gr.Dropdown(multiselect=True, scale=4)
preview_btn = gr.Button(interactive=False, scale=1)
data_preview_btn = gr.Button(interactive=False, scale=1)
preview_box, preview_count, preview_samples, close_btn = create_preview_box()
dataset_dir.change(list_dataset, [dataset_dir], [dataset])
dataset.change(can_preview, [dataset_dir, dataset], [preview_btn])
preview_btn.click(
dataset.change(can_preview, [dataset_dir, dataset], [data_preview_btn])
data_preview_btn.click(
get_preview,
[dataset_dir, dataset],
[preview_count, preview_samples, preview_box],
@@ -61,15 +61,12 @@ def create_sft_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict[
resume_lora_training = gr.Checkbox(value=True, scale=1)
with gr.Row():
preview_script_btn = gr.Button()
cmd_preview_btn = gr.Button()
start_btn = gr.Button()
stop_btn = gr.Button()
with gr.Row():
with gr.Column(scale=3):
with gr.Box():
preview_script_box = gr.Textbox()
with gr.Row():
output_dir = gr.Textbox()
@@ -82,82 +79,45 @@ def create_sft_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict[
with gr.Column(scale=1):
loss_viewer = gr.Plot()
preview_script_btn.click(
runner.preview_sft_script,
[
top_elems["lang"],
top_elems["model_name"],
top_elems["checkpoints"],
top_elems["finetuning_type"],
top_elems["quantization_bit"],
top_elems["template"],
top_elems["source_prefix"],
dataset_dir,
dataset,
max_source_length,
max_target_length,
learning_rate,
num_train_epochs,
max_samples,
batch_size,
gradient_accumulation_steps,
lr_scheduler_type,
max_grad_norm,
val_size,
logging_steps,
save_steps,
warmup_steps,
compute_type,
padding_side,
lora_rank,
lora_dropout,
lora_target,
resume_lora_training,
output_dir
],
[
preview_script_box
]
)
input_list = [
top_elems["lang"],
top_elems["model_name"],
top_elems["checkpoints"],
top_elems["finetuning_type"],
top_elems["quantization_bit"],
top_elems["template"],
top_elems["source_prefix"],
dataset_dir,
dataset,
max_source_length,
max_target_length,
learning_rate,
num_train_epochs,
max_samples,
batch_size,
gradient_accumulation_steps,
lr_scheduler_type,
max_grad_norm,
val_size,
logging_steps,
save_steps,
warmup_steps,
compute_type,
padding_side,
lora_rank,
lora_dropout,
lora_target,
resume_lora_training,
output_dir
]
start_btn.click(
runner.run_train,
[
top_elems["lang"],
top_elems["model_name"],
top_elems["checkpoints"],
top_elems["finetuning_type"],
top_elems["quantization_bit"],
top_elems["template"],
top_elems["source_prefix"],
dataset_dir,
dataset,
max_source_length,
max_target_length,
learning_rate,
num_train_epochs,
max_samples,
batch_size,
gradient_accumulation_steps,
lr_scheduler_type,
max_grad_norm,
val_size,
logging_steps,
save_steps,
warmup_steps,
compute_type,
padding_side,
lora_rank,
lora_dropout,
lora_target,
resume_lora_training,
output_dir
],
[
output_box,
process_bar
]
)
output_list = [
output_box,
process_bar
]
cmd_preview_btn.click(runner.preview_train, input_list, output_list)
start_btn.click(runner.run_train, input_list, output_list)
stop_btn.click(runner.set_abort, queue=False)
process_bar.change(
@@ -167,7 +127,7 @@ def create_sft_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict[
return dict(
dataset_dir=dataset_dir,
dataset=dataset,
preview_btn=preview_btn,
data_preview_btn=data_preview_btn,
preview_count=preview_count,
preview_samples=preview_samples,
close_btn=close_btn,
@@ -192,11 +152,10 @@ def create_sft_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict[
lora_dropout=lora_dropout,
lora_target=lora_target,
resume_lora_training=resume_lora_training,
cmd_preview_btn=cmd_preview_btn,
start_btn=start_btn,
stop_btn=stop_btn,
output_dir=output_dir,
output_box=output_box,
loss_viewer=loss_viewer,
preview_script_btn=preview_script_btn,
preview_script_box=preview_script_box
loss_viewer=loss_viewer
)