mirror of
https://github.com/hiyouga/LLaMA-Factory.git
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71 lines
2.5 KiB
Python
71 lines
2.5 KiB
Python
# Copyright 2025 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from collections.abc import Generator
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from gradio.components import Component
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class Manager:
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r"""A class to manage all the gradio components in Web UI."""
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def __init__(self) -> None:
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self._id_to_elem: dict[str, Component] = {}
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self._elem_to_id: dict[Component, str] = {}
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def add_elems(self, tab_name: str, elem_dict: dict[str, "Component"]) -> None:
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r"""Add elements to manager."""
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for elem_name, elem in elem_dict.items():
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elem_id = f"{tab_name}.{elem_name}"
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self._id_to_elem[elem_id] = elem
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self._elem_to_id[elem] = elem_id
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def get_elem_list(self) -> list["Component"]:
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r"""Return the list of all elements."""
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return list(self._id_to_elem.values())
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def get_elem_iter(self) -> Generator[tuple[str, "Component"], None, None]:
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r"""Return an iterator over all elements with their names."""
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for elem_id, elem in self._id_to_elem.items():
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yield elem_id.split(".")[-1], elem
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def get_elem_by_id(self, elem_id: str) -> "Component":
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r"""Get element by id.
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Example: top.lang, train.dataset
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"""
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return self._id_to_elem[elem_id]
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def get_id_by_elem(self, elem: "Component") -> str:
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r"""Get id by element."""
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return self._elem_to_id[elem]
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def get_base_elems(self) -> set["Component"]:
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r"""Get the base elements that are commonly used."""
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return {
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self._id_to_elem["top.lang"],
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self._id_to_elem["top.model_name"],
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self._id_to_elem["top.model_path"],
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self._id_to_elem["top.finetuning_type"],
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self._id_to_elem["top.checkpoint_path"],
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self._id_to_elem["top.quantization_bit"],
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self._id_to_elem["top.quantization_method"],
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self._id_to_elem["top.template"],
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self._id_to_elem["top.rope_scaling"],
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self._id_to_elem["top.booster"],
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}
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