rename package

Former-commit-id: a07ff0c083558cfe6f474d13027642d3052fee08

src/llamafactory/webui/components/eval.py

@@ -0,0 +1,79 @@
+from typing import TYPE_CHECKING, Dict
+
+from ...extras.packages import is_gradio_available
+from ..common import DEFAULT_DATA_DIR, list_dataset
+from .data import create_preview_box
+
+
+if is_gradio_available():
+    import gradio as gr
+
+
+if TYPE_CHECKING:
+    from gradio.components import Component
+
+    from ..engine import Engine
+
+
+def create_eval_tab(engine: "Engine") -> Dict[str, "Component"]:
+    input_elems = engine.manager.get_base_elems()
+    elem_dict = dict()
+
+    with gr.Row():
+        dataset_dir = gr.Textbox(value=DEFAULT_DATA_DIR, scale=2)
+        dataset = gr.Dropdown(multiselect=True, allow_custom_value=True, scale=4)
+        preview_elems = create_preview_box(dataset_dir, dataset)
+
+    input_elems.update({dataset_dir, dataset})
+    elem_dict.update(dict(dataset_dir=dataset_dir, dataset=dataset, **preview_elems))
+
+    with gr.Row():
+        cutoff_len = gr.Slider(minimum=4, maximum=65536, value=1024, step=1)
+        max_samples = gr.Textbox(value="100000")
+        batch_size = gr.Slider(minimum=1, maximum=1024, value=2, step=1)
+        predict = gr.Checkbox(value=True)
+
+    input_elems.update({cutoff_len, max_samples, batch_size, predict})
+    elem_dict.update(dict(cutoff_len=cutoff_len, max_samples=max_samples, batch_size=batch_size, predict=predict))
+
+    with gr.Row():
+        max_new_tokens = gr.Slider(minimum=8, maximum=4096, value=512, step=1)
+        top_p = gr.Slider(minimum=0.01, maximum=1, value=0.7, step=0.01)
+        temperature = gr.Slider(minimum=0.01, maximum=1.5, value=0.95, step=0.01)
+        output_dir = gr.Textbox()
+
+    input_elems.update({max_new_tokens, top_p, temperature, output_dir})
+    elem_dict.update(dict(max_new_tokens=max_new_tokens, top_p=top_p, temperature=temperature, output_dir=output_dir))
+
+    with gr.Row():
+        cmd_preview_btn = gr.Button()
+        start_btn = gr.Button(variant="primary")
+        stop_btn = gr.Button(variant="stop")
+
+    with gr.Row():
+        resume_btn = gr.Checkbox(visible=False, interactive=False)
+        progress_bar = gr.Slider(visible=False, interactive=False)
+
+    with gr.Row():
+        output_box = gr.Markdown()
+
+    output_elems = [output_box, progress_bar]
+    elem_dict.update(
+        dict(
+            cmd_preview_btn=cmd_preview_btn,
+            start_btn=start_btn,
+            stop_btn=stop_btn,
+            resume_btn=resume_btn,
+            progress_bar=progress_bar,
+            output_box=output_box,
+        )
+    )
+
+    cmd_preview_btn.click(engine.runner.preview_eval, input_elems, output_elems, concurrency_limit=None)
+    start_btn.click(engine.runner.run_eval, input_elems, output_elems)
+    stop_btn.click(engine.runner.set_abort)
+    resume_btn.change(engine.runner.monitor, outputs=output_elems, concurrency_limit=None)
+
+    dataset_dir.change(list_dataset, [dataset_dir], [dataset], queue=False)
+
+    return elem_dict