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from typing import TYPE_CHECKING, Dict, Generator, List
import gradio as gr
from ...train import export_model
from ..common import get_save_dir
from ..locales import ALERTS
if TYPE_CHECKING:
from gradio.components import Component
from ..engine import Engine
GPTQ_BITS = ["8", "4", "3", "2"]
def save_model(
lang: str,
model_name: str,
model_path: str,
adapter_path: List[str],
finetuning_type: str,
template: str,
max_shard_size: int,
export_quantization_bit: int,
export_quantization_dataset: str,
export_dir: str,
) -> Generator[str, None, None]:
error = ""
if not model_name:
error = ALERTS["err_no_model"][lang]
elif not model_path:
error = ALERTS["err_no_path"][lang]
elif not export_dir:
error = ALERTS["err_no_export_dir"][lang]
elif export_quantization_bit in GPTQ_BITS and not export_quantization_dataset:
error = ALERTS["err_no_dataset"][lang]
elif export_quantization_bit not in GPTQ_BITS and not adapter_path:
error = ALERTS["err_no_adapter"][lang]
if error:
gr.Warning(error)
yield error
return
if adapter_path:
adapter_name_or_path = ",".join(
[get_save_dir(model_name, finetuning_type, adapter) for adapter in adapter_path]
)
else:
adapter_name_or_path = None
args = dict(
model_name_or_path=model_path,
adapter_name_or_path=adapter_name_or_path,
finetuning_type=finetuning_type,
template=template,
export_dir=export_dir,
export_size=max_shard_size,
export_quantization_bit=int(export_quantization_bit) if export_quantization_bit in GPTQ_BITS else None,
export_quantization_dataset=export_quantization_dataset,
)
yield ALERTS["info_exporting"][lang]
export_model(args)
yield ALERTS["info_exported"][lang]
def create_export_tab(engine: "Engine") -> Dict[str, "Component"]:
with gr.Row():
max_shard_size = gr.Slider(value=1, minimum=1, maximum=100)
export_quantization_bit = gr.Dropdown(choices=["none", "8", "4", "3", "2"], value="none")
export_quantization_dataset = gr.Textbox(value="data/c4_demo.json")
export_dir = gr.Textbox()
export_btn = gr.Button()
info_box = gr.Textbox(show_label=False, interactive=False)
export_btn.click(
save_model,
[
engine.manager.get_elem_by_name("top.lang"),
engine.manager.get_elem_by_name("top.model_name"),
engine.manager.get_elem_by_name("top.model_path"),
engine.manager.get_elem_by_name("top.adapter_path"),
engine.manager.get_elem_by_name("top.finetuning_type"),
engine.manager.get_elem_by_name("top.template"),
max_shard_size,
export_quantization_bit,
export_quantization_dataset,
export_dir,
],
[info_box],
)
return dict(
max_shard_size=max_shard_size,
export_quantization_bit=export_quantization_bit,
export_quantization_dataset=export_quantization_dataset,
export_dir=export_dir,
export_btn=export_btn,
info_box=info_box,
)
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