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Commit ec767666 authored by Baber's avatar Baber
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overload Task methods if callable in yaml dict

parent 2009ec4b
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Showing with 80 additions and 73 deletions
lm_eval/api/filter.py
View file @ ec767666
from abc import ABC, abstractmethod
from collections.abc import Iterable
from dataclasses import dataclass
from typing import Protocol, runtime_checkable
from lm_eval.api.instance import Instance
class Filter(ABC):
@runtime_checkable
class Filter(Protocol):
"""
Filter classes operate on a per-task level.
They take all model outputs (`instance.resps` for all `task.instances`)
......@@ -19,7 +20,6 @@ class Filter(ABC):
Can define custom behavior here, if an individual instantiation of a Filter class should have state.
"""
@abstractmethod
def apply(
self, resps: Iterable[list[str]], docs: Iterable[dict]
) -> Iterable[list[str]]:
......
lm_eval/api/task.py
View file @ ec767666
......@@ -7,6 +7,8 @@ import random
import re
from collections.abc import Callable
from copy import deepcopy
from functools import cached_property
from types import MethodType
from typing import TYPE_CHECKING, Any, Literal, overload
import datasets
......@@ -143,14 +145,17 @@ class Task(abc.ABC):
"""Returns the TaskConfig associated with this class."""
return self._config
@property
def has_training_docs(self) -> bool:
"""Whether the task has a training set"""
raise NotImplementedError
@property
def has_validation_docs(self) -> bool:
"""Whether the task has a validation set"""
raise NotImplementedError
@property
def has_test_docs(self) -> bool:
"""Whether the task has a test set"""
raise NotImplementedError
......@@ -181,9 +186,9 @@ class Task(abc.ABC):
:return: Iterable[obj]
A iterable of any object, that doc_to_text can handle
"""
if self.has_training_docs():
if self.has_training_docs:
return self.training_docs()
elif self.has_validation_docs():
elif self.has_validation_docs:
return self.validation_docs()
else:
if self.config.num_fewshot and self.config.num_fewshot > 0:
......@@ -211,7 +216,7 @@ class Task(abc.ABC):
"""
return self._instances
def fewshot_examples(self, k, rnd) -> Iterable[dict]:
def fewshot_examples(self, k: int, rnd) -> Iterable[dict]:
if self._training_docs is None:
self._training_docs = list(self.training_docs())
......@@ -449,13 +454,13 @@ class Task(abc.ABC):
labeled_examples = ""
else:
# for sets with no training docs, draw from other set *but ensure no overlap with current doc*
if self.has_training_docs():
if self.has_training_docs:
fewshotex = self.fewshot_examples(k=num_fewshot, rnd=rnd)
else:
if self._fewshot_docs is None:
self._fewshot_docs = list(
self.validation_docs()
if self.has_validation_docs()
if self.has_validation_docs
else self.test_docs()
)
......@@ -528,9 +533,9 @@ class Task(abc.ABC):
@property
def eval_docs(self) -> datasets.Dataset | Iterable[dict]:
if self.has_test_docs():
if self.has_test_docs:
return self.test_docs()
elif self.has_validation_docs():
elif self.has_validation_docs:
return self.validation_docs()
else:
raise ValueError(
......@@ -587,7 +592,7 @@ class ConfigurableTask(Task):
# Use new configurations if there was no preconfiguration
if self.config is None:
self._config = TaskConfig(**config)
self._config = TaskConfig.from_yaml(config)
# Overwrite configs
else:
if config is not None:
......@@ -730,17 +735,20 @@ class ConfigurableTask(Task):
**self.config.dataset_kwargs,
)
@cached_property
def has_training_docs(self) -> bool:
return self.config.training_split is not None
@cached_property
def has_validation_docs(self) -> bool:
return self.config.validation_split is not None
@cached_property
def has_test_docs(self) -> bool:
return self.config.test_split is not None
def training_docs(self) -> DataSet | None:
if self.has_training_docs():
if self.has_training_docs:
if self.config.process_docs is not None:
return self.config.process_docs(
self.dataset[self.config.training_split]
......@@ -748,7 +756,7 @@ class ConfigurableTask(Task):
return self.dataset[self.config.training_split]
def validation_docs(self) -> DataSet | None:
if self.has_validation_docs():
if self.has_validation_docs:
if self.config.process_docs is not None:
return self.config.process_docs(
self.dataset[self.config.validation_split]
......@@ -756,7 +764,7 @@ class ConfigurableTask(Task):
return self.dataset[self.config.validation_split]
def test_docs(self) -> DataSet | None:
if self.has_test_docs():
if self.has_test_docs:
if self.config.process_docs is not None:
return self.config.process_docs(self.dataset[self.config.test_split])
return self.dataset[self.config.test_split]
......@@ -1011,23 +1019,16 @@ class ConfigurableTask(Task):
# if self.prompt is not None:
# doc_to_text = self.prompt
doc_to_text = doc_to_text or self.config.doc_to_text
if isinstance(doc_to_text, int):
return doc_to_text
if doc_to_text in doc:
return doc[doc_to_text]
elif isinstance(doc_to_text, str):
if doc_to_text in self.features:
# if self.config.doc_to_choice is not None:
# return self.doc_to_choice(doc)[doc[doc_to_text]]
# else:
return doc[doc_to_text]
text_string = utils.apply_template(doc_to_text, doc)
if text_string.isdigit() and self.config.doc_to_choice is not None:
return ast.literal_eval(text_string)
else:
text_string = utils.apply_template(doc_to_text, doc)
if text_string.isdigit() and self.config.doc_to_choice is not None:
return ast.literal_eval(text_string)
else:
return text_string
elif callable(doc_to_text):
return doc_to_text(doc)
return text_string
elif isinstance(doc_to_text, int):
return doc_to_text
# Used when applying a Promptsource template
# elif hasattr(doc_to_text, "apply"):
# applied_prompt = doc_to_text.apply(doc)
......@@ -1062,38 +1063,31 @@ class ConfigurableTask(Task):
def doc_to_target(self, doc: dict, doc_to_target=None) -> int | str | list[int]:
# if self.prompt is not None:
# doc_to_target = self.prompt
if doc_to_target is not None:
doc_to_target = doc_to_target
else:
doc_to_target = self.config.doc_to_target
if isinstance(doc_to_target, int):
return doc_to_target
doc_to_target = doc_to_target or self.config.doc_to_target
if doc_to_target in doc:
return doc[doc_to_target]
elif isinstance(doc_to_target, str):
if doc_to_target in self.features:
# if self.config.doc_to_choice is not None:
# return self.doc_to_choice(doc)[doc[doc_to_target]]
# else:
return doc[doc_to_target]
target_string = utils.apply_template(doc_to_target, doc)
if target_string.isdigit() and self.config.doc_to_choice is not None:
return ast.literal_eval(target_string)
# elif (
# len(target_string) >= 2
# and (target_string[0] == "[")
# and (target_string[-1] == "]")
# ):
# try:
# return ast.literal_eval(target_string)
# except (SyntaxError, ValueError):
# return target_string
else:
target_string = utils.apply_template(doc_to_target, doc)
if target_string.isdigit() and self.config.doc_to_choice is not None:
return ast.literal_eval(target_string)
elif (
len(target_string) >= 2
and (target_string[0] == "[")
and (target_string[-1] == "]")
):
try:
return ast.literal_eval(target_string)
except (SyntaxError, ValueError):
return target_string
else:
return target_string
elif isinstance(doc_to_target, list):
return target_string
elif isinstance(doc_to_target, (int, list)):
return doc_to_target
elif callable(doc_to_target):
return doc_to_target(doc)
# elif isinstance(doc_to_target, list):
# return doc_to_target
# elif callable(doc_to_target):
# return doc_to_target(doc)
# # Used when applying a Promptsource template
# elif hasattr(doc_to_target, "apply"):
# applied_prompt = doc_to_target.apply(doc)
......@@ -1138,16 +1132,14 @@ class ConfigurableTask(Task):
doc_to_choice = self.config.doc_to_choice
if isinstance(doc_to_choice, str):
if doc_to_choice in self.features:
if doc_to_choice in doc:
return doc[doc_to_choice]
else:
return ast.literal_eval(utils.apply_template(doc_to_choice, doc))
elif isinstance(doc_to_choice, list):
return doc_to_choice
elif isinstance(doc_to_choice, dict):
return list(doc_to_choice.values())
elif callable(doc_to_choice):
return doc_to_choice(doc)
# elif isinstance(doc_to_choice, dict):
# return list(doc_to_choice.values())
# elif hasattr(doc_to_choice, "get_answer_choices_list"):
# return doc_to_choice.get_answer_choices_list(doc)
else:
......@@ -1225,7 +1217,7 @@ class ConfigurableTask(Task):
def doc_to_prefix(self, doc: dict) -> str | None:
if (gen_prefix := self.config.gen_prefix) is not None:
if gen_prefix in self.features:
if gen_prefix in doc:
return doc[gen_prefix]
else:
return utils.apply_template(gen_prefix, doc)
......@@ -1333,9 +1325,6 @@ class ConfigurableTask(Task):
)
def process_results(self, doc: dict, results: list) -> dict[str, Any]:
if callable(self.config.process_results):
return self.config.process_results(doc, results)
result_dict = {}
use_metric = list(m.metric_name for m in self.config._metric_list)
if self.OUTPUT_TYPE == "loglikelihood":
......
lm_eval/config/task.py
View file @ ec767666
......@@ -10,7 +10,7 @@ import datasets
from lm_eval.api.filter import FilterEnsemble
from lm_eval.api.instance import OutputType
from lm_eval.config.metric import MetricConfig
from lm_eval.config.utils import maybe_serialize
from lm_eval.config.utils import doc_to_closure, maybe_serialize
if TYPE_CHECKING:
......@@ -179,6 +179,7 @@ class TaskConfig:
_filter_list: list[FilterConfig] = field(default_factory=list)
# ds_cfg: DatasetConfig = field(init=False)
fewshot_cfg: FewshotConfig = field(init=False)
_fn: dict[str, Callable] = field(default_factory=dict)
def __post_init__(self) -> None:
### ---setup generation kwargs--- ###
......@@ -363,7 +364,8 @@ class TaskConfig:
@classmethod
def from_yaml(cls, data: dict[str, Any]) -> TaskConfig:
"""Create a TaskConfig instance from a YAML-like dictionary."""
return cls(**data)
fn = {k: doc_to_closure(v) for k, v in data.items() if callable(v)}
return cls(**data, _fn=fn)
@classmethod
def from_template(cls, template: TemplateConfig, **kwargs) -> TaskConfig:
......
lm_eval/config/utils.py
View file @ ec767666
from __future__ import annotations
from functools import wraps
from inspect import getsource
from typing import Any, Callable
from typing import Any, Callable, TypeVar
T = TypeVar("T")
def serialize_callable(
value: Callable[..., Any] | str, keep_callable=False
) -> Callable[..., Any] | str:
value: Callable[..., T] | str, keep_callable=False
) -> Callable[..., T] | str:
"""Serializes a given function or string.
If 'keep_callable' is True, the original callable is returned.
......@@ -22,7 +26,9 @@ def serialize_callable(
return str(value)
def maybe_serialize(val: Callable | Any, keep_callable=False) -> Callable | Any:
def maybe_serialize(
val: Callable[..., T] | Any, keep_callable=False
) -> Callable[..., T] | Any:
"""Conditionally serializes a value if it is callable."""
return (
......@@ -41,3 +47,13 @@ def create_mc_choices(choices: list[str], choice_delimiter: str | None = "\n") -
formatted_choices = [f"{chr(65 + i)}. {choice}" for i, choice in enumerate(choices)]
return choice_delimiter.join(formatted_choices)
def doc_to_closure(fn: Callable[..., T]) -> Callable[..., T]:
"""Closure that allows the function to be called with 'self'."""
@wraps(fn)
def closure(self: Any, *args, **kwargs):
return fn(*args, **kwargs)
return closure
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