Files
llm_trainer/src/llmtuner/webui/manager.py
2024-03-30 20:37:08 +08:00

56 lines
1.8 KiB
Python

from typing import TYPE_CHECKING, Dict, Generator, List, Set, Tuple
if TYPE_CHECKING:
from gradio.components import Component
class Manager:
def __init__(self) -> None:
self._elem_dicts: Dict[str, Dict[str, "Component"]] = {}
def add_elem_dict(self, tab_name: str, elem_dict: Dict[str, "Component"]) -> None:
r"""
Adds a elem dict.
"""
self._elem_dicts[tab_name] = elem_dict
def get_elem_list(self) -> List["Component"]:
r"""
Returns the list of all elements.
"""
return [elem for elem_dict in self._elem_dicts.values() for elem in elem_dict.values()]
def get_elem_iter(self) -> Generator[Tuple[str, "Component"], None, None]:
r"""
Returns an iterator over all elements with their names.
"""
for elem_dict in self._elem_dicts.values():
for elem_name, elem in elem_dict.items():
yield elem_name, elem
def get_elem_by_id(self, elem_id: str) -> "Component":
r"""
Gets element by id.
Example: top.lang, train.dataset
"""
tab_name, elem_name = elem_id.split(".")
return self._elem_dicts[tab_name][elem_name]
def get_base_elems(self) -> Set["Component"]:
r"""
Gets the base elements that are commonly used.
"""
return {
self._elem_dicts["top"]["lang"],
self._elem_dicts["top"]["model_name"],
self._elem_dicts["top"]["model_path"],
self._elem_dicts["top"]["finetuning_type"],
self._elem_dicts["top"]["adapter_path"],
self._elem_dicts["top"]["quantization_bit"],
self._elem_dicts["top"]["template"],
self._elem_dicts["top"]["rope_scaling"],
self._elem_dicts["top"]["booster"],
}