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from typing import TYPE_CHECKING, Dict
import gradio as gr
from llmtuner.webui.common import list_dataset, DEFAULT_DATA_DIR
from llmtuner.webui.components.data import create_preview_box
from llmtuner.webui.utils import can_preview, get_preview
if TYPE_CHECKING:
from gradio.components import Component
from llmtuner.webui.runner import Runner
def create_eval_tab(top_elems: Dict[str, "Component"], runner: "Runner") -> Dict[str, "Component"]:
with gr.Row():
dataset_dir = gr.Textbox(value=DEFAULT_DATA_DIR, scale=2)
dataset = gr.Dropdown(multiselect=True, scale=4)
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], [data_preview_btn])
data_preview_btn.click(
get_preview,
[dataset_dir, dataset],
[preview_count, preview_samples, preview_box],
queue=False
)
with gr.Row():
cutoff_len = gr.Slider(value=1024, minimum=4, maximum=8192, step=1)
max_samples = gr.Textbox(value="100000")
batch_size = gr.Slider(value=8, minimum=1, maximum=512, step=1)
predict = gr.Checkbox(value=True)
with gr.Row():
max_new_tokens = gr.Slider(10, 2048, value=128, step=1)
top_p = gr.Slider(0.01, 1, value=0.7, step=0.01)
temperature = gr.Slider(0.01, 1.5, value=0.95, step=0.01)
with gr.Row():
cmd_preview_btn = gr.Button()
start_btn = gr.Button()
stop_btn = gr.Button()
with gr.Row():
process_bar = gr.Slider(visible=False, interactive=False)
with gr.Box():
output_box = gr.Markdown()
input_components = [
top_elems["lang"],
top_elems["model_name"],
top_elems["checkpoints"],
top_elems["finetuning_type"],
top_elems["quantization_bit"],
top_elems["template"],
top_elems["system_prompt"],
dataset_dir,
dataset,
cutoff_len,
max_samples,
batch_size,
predict,
max_new_tokens,
top_p,
temperature
]
output_components = [
output_box,
process_bar
]
cmd_preview_btn.click(runner.preview_eval, input_components, output_components)
start_btn.click(runner.run_eval, input_components, output_components)
stop_btn.click(runner.set_abort, queue=False)
return dict(
dataset_dir=dataset_dir,
dataset=dataset,
data_preview_btn=data_preview_btn,
preview_count=preview_count,
preview_samples=preview_samples,
close_btn=close_btn,
cutoff_len=cutoff_len,
max_samples=max_samples,
batch_size=batch_size,
predict=predict,
max_new_tokens=max_new_tokens,
top_p=top_p,
temperature=temperature,
cmd_preview_btn=cmd_preview_btn,
start_btn=start_btn,
stop_btn=stop_btn,
output_box=output_box
)
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