hiyouga af37ac077c support dev set in web ui
Former-commit-id: fe2887ca1304e5b5cfd7fbd820a9a0c8dedd23ef
2023-07-18 20:40:49 +08:00

74 lines
2.4 KiB
Python

from typing import Dict
import gradio as gr
from gradio.components import Component
from llmtuner.webui.common import list_dataset, DEFAULT_DATA_DIR
from llmtuner.webui.components.data import create_preview_box
from llmtuner.webui.runner import Runner
from llmtuner.webui.utils import can_preview, get_preview
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)
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(get_preview, [dataset_dir, dataset], [preview_count, preview_samples, preview_box])
with gr.Row():
max_source_length = gr.Slider(value=512, minimum=4, maximum=4096, step=1)
max_target_length = gr.Slider(value=512, minimum=4, maximum=4096, 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():
start_btn = gr.Button()
stop_btn = gr.Button()
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]
)
stop_btn.click(runner.set_abort, queue=False)
return dict(
dataset_dir=dataset_dir,
dataset=dataset,
preview_btn=preview_btn,
preview_count=preview_count,
preview_samples=preview_samples,
close_btn=close_btn,
max_source_length=max_source_length,
max_target_length=max_target_length,
max_samples=max_samples,
batch_size=batch_size,
predict=predict,
start_btn=start_btn,
stop_btn=stop_btn,
output_box=output_box
)