Download spatial-model/GeoThinker/src/lmms_eval/api/group.py from hyin-ustc/embodied-eval: direct link, hf CLI and curl.
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https://huggingface.co/datasets/hyin-ustc/embodied-eval/resolve/main/spatial-model/GeoThinker/src/lmms_eval/api/group.py
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curl -L -o group.py https://huggingface.co/datasets/hyin-ustc/embodied-eval/resolve/main/spatial-model/GeoThinker/src/lmms_eval/api/group.py
3.53 kB
| import abc | |
| from dataclasses import asdict, dataclass | |
| from inspect import getsource | |
| from typing import Any, Callable, List, Optional, Union | |
| class AggMetricConfig(dict): | |
| metric: Optional[str] = None | |
| aggregation: Optional[str] = "mean" | |
| weight_by_size: Optional[str] = False | |
| # list of filter names which should be incorporated into the aggregated metric. | |
| filter_list: Optional[Union[str, list]] = "none" | |
| def __post_init__(self): | |
| if self.aggregation != "mean" and not callable(self.aggregation): | |
| raise ValueError(f"Currently, 'mean' is the only pre-defined aggregation across groups' subtasks. Got '{self.aggregation}'.") | |
| if isinstance(self.filter_list, str): | |
| self.filter_list = [self.filter_list] | |
| class GroupConfig(dict): | |
| group: Optional[str] = None | |
| group_alias: Optional[str] = None | |
| task: Optional[Union[str, list]] = None | |
| aggregate_metric_list: Optional[Union[List[AggMetricConfig], AggMetricConfig, dict]] = None | |
| metadata: Optional[dict] = None # by default, not used in the code. allows for users to pass arbitrary info to tasks | |
| def __getitem__(self, item): | |
| return getattr(self, item) | |
| def __setitem__(self, item, value): | |
| return setattr(self, item, value) | |
| def __post_init__(self): | |
| if self.aggregate_metric_list is not None: | |
| if isinstance(self.aggregate_metric_list, dict): | |
| self.aggregate_metric_list = [self.aggregate_metric_list] | |
| self.aggregate_metric_list = [AggMetricConfig(**item) if isinstance(item, dict) else item for item in self.aggregate_metric_list] | |
| def to_dict(self, keep_callable: bool = False) -> dict: | |
| """dumps the current config as a dictionary object, as a printable format. | |
| null fields will not be printed. | |
| Used for dumping results alongside full task configuration | |
| :return: dict | |
| A printable dictionary version of the TaskConfig object. | |
| # TODO: should any default value in the TaskConfig not be printed? | |
| """ | |
| cfg_dict = asdict(self) | |
| # remove values that are `None` | |
| for k, v in list(cfg_dict.items()): | |
| if callable(v): | |
| cfg_dict[k] = self.serialize_function(v, keep_callable=keep_callable) | |
| return cfg_dict | |
| def serialize_function(self, value: Union[Callable, str], keep_callable=False) -> Union[Callable, str]: | |
| """Serializes a given function or string. | |
| If 'keep_callable' is True, the original callable is returned. | |
| Otherwise, attempts to return the source code of the callable using 'getsource'. | |
| """ | |
| if keep_callable: | |
| return value | |
| else: | |
| try: | |
| return getsource(value) | |
| except (TypeError, OSError): | |
| return str(value) | |
| class ConfigurableGroup(abc.ABC): | |
| def __init__( | |
| self, | |
| config: Optional[dict] = None, | |
| ) -> None: | |
| self._config = GroupConfig(**config) | |
| def group(self): | |
| return self._config.group | |
| def group_alias(self): | |
| return self._config.group_alias | |
| def version(self): | |
| return self._config.version | |
| def config(self): | |
| return self._config.to_dict() | |
| def group_name(self) -> Any: | |
| return self._config.group | |
| def __repr__(self): | |
| return f"ConfigurableGroup(group={self.group}," f"group_alias={self.group_alias})" | |