release v0.1.0

Former-commit-id: 63c8d3a17cb18f0d8a8e37bfa147daf5bdd28ea9
2023-07-18 00:18:25 +08:00
parent c08ff734a7
commit eac7f97337
30 changed files with 1513 additions and 309 deletions
--- a/src/llmtuner/webui/components/sft.py
+++ b/src/llmtuner/webui/components/sft.py
@@ -0,0 +1,94 @@
+from typing import Dict
+from transformers.trainer_utils import SchedulerType
+
+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, gen_plot
+
+
+def create_sft_tab(top_elems: Dict[str, Component], runner: Runner) -> Dict[str, Component]:
+    with gr.Row():
+        dataset_dir = gr.Textbox(value=DEFAULT_DATA_DIR, interactive=True, scale=1)
+        dataset = gr.Dropdown(multiselect=True, interactive=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():
+        learning_rate = gr.Textbox(value="5e-5", interactive=True)
+        num_train_epochs = gr.Textbox(value="3.0", interactive=True)
+        max_samples = gr.Textbox(value="100000", interactive=True)
+        quantization_bit = gr.Dropdown([8, 4])
+
+    with gr.Row():
+        batch_size = gr.Slider(value=4, minimum=1, maximum=128, step=1, interactive=True)
+        gradient_accumulation_steps = gr.Slider(value=4, minimum=1, maximum=32, step=1, interactive=True)
+        lr_scheduler_type = gr.Dropdown(
+            value="cosine", choices=[scheduler.value for scheduler in SchedulerType], interactive=True
+        )
+        fp16 = gr.Checkbox(value=True)
+
+    with gr.Row():
+        logging_steps = gr.Slider(value=5, minimum=5, maximum=1000, step=5, interactive=True)
+        save_steps = gr.Slider(value=100, minimum=10, maximum=2000, step=10, interactive=True)
+
+    with gr.Row():
+        start_btn = gr.Button()
+        stop_btn = gr.Button()
+
+    with gr.Row():
+        with gr.Column(scale=4):
+            output_dir = gr.Textbox(interactive=True)
+            output_box = gr.Markdown()
+
+        with gr.Column(scale=1):
+            loss_viewer = gr.Plot()
+
+    start_btn.click(
+        runner.run_train,
+        [
+            top_elems["lang"], top_elems["model_name"], top_elems["checkpoints"],
+            top_elems["finetuning_type"], top_elems["template"],
+            dataset, dataset_dir, learning_rate, num_train_epochs, max_samples,
+            fp16, quantization_bit, batch_size, gradient_accumulation_steps,
+            lr_scheduler_type, logging_steps, save_steps, output_dir
+        ],
+        [output_box]
+    )
+    stop_btn.click(runner.set_abort, queue=False)
+
+    output_box.change(
+        gen_plot, [top_elems["model_name"], top_elems["finetuning_type"], output_dir], loss_viewer, 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,
+        learning_rate=learning_rate,
+        num_train_epochs=num_train_epochs,
+        max_samples=max_samples,
+        quantization_bit=quantization_bit,
+        batch_size=batch_size,
+        gradient_accumulation_steps=gradient_accumulation_steps,
+        lr_scheduler_type=lr_scheduler_type,
+        fp16=fp16,
+        logging_steps=logging_steps,
+        save_steps=save_steps,
+        start_btn=start_btn,
+        stop_btn=stop_btn,
+        output_dir=output_dir,
+        output_box=output_box,
+        loss_viewer=loss_viewer
+    )