| from functools import partial |
| from typing import TYPE_CHECKING, Iterable, Optional, Union |
|
|
| import datasets |
|
|
|
|
| if TYPE_CHECKING: |
| from random import Random |
|
|
| from lm_eval.api.task import ConfigurableTask, Task |
|
|
|
|
| class ContextSampler: |
| def __init__( |
| self, |
| docs: list[dict], |
| task: Union["Task", "ConfigurableTask"], |
| fewshot_indices: Optional[Iterable] = None, |
| rnd: Optional["Random"] = None, |
| ) -> None: |
| self.rnd = rnd |
| if not self.rnd: |
| raise ValueError( |
| "A `random.Random` generator argument must be provided to `rnd` of FewShotSampler!" |
| ) |
|
|
| self.task = task |
| self.config = task._config |
|
|
| self.target_delimiter = self.config.target_delimiter |
| self.fewshot_delimiter = self.config.fewshot_delimiter |
|
|
| if ( |
| self.config.fewshot_config is not None |
| and self.config.fewshot_config.get("doc_to_text", None) is not None |
| ): |
| self.doc_to_text = partial( |
| self.task.doc_to_text, |
| doc_to_text=self.config.fewshot_config.get("doc_to_text", None), |
| ) |
| else: |
| self.doc_to_text = self.task.doc_to_text |
|
|
| if ( |
| self.config.fewshot_config is not None |
| and self.config.fewshot_config.get("doc_to_target", None) is not None |
| ): |
| self.doc_to_target = partial( |
| self.task.doc_to_target, |
| doc_to_target=self.config.fewshot_config.get("doc_to_target", None), |
| ) |
| else: |
| self.doc_to_target = self.task.doc_to_target |
|
|
| if ( |
| self.config.fewshot_config is not None |
| and self.config.fewshot_config.get("doc_to_choice", None) is not None |
| ): |
| self.doc_to_choice = partial( |
| self.task.doc_to_choice, |
| doc_to_choice=self.config.fewshot_config.get("doc_to_choice", None), |
| ) |
| else: |
| self.doc_to_choice = self.task.doc_to_choice |
|
|
| self.docs = docs |
| if fewshot_indices: |
| if not isinstance(self.docs, datasets.Dataset): |
| raise ValueError( |
| "Got `fewshot_indices` but fewshot_docs are not a HF dataset. Don't use both `fewshot_indices` and a user-defined few-shot sample list simultaneously" |
| ) |
| self.docs = self.docs.select(fewshot_indices) |
|
|
| def get_context(self, doc: dict, num_fewshot: int, gen_prefix: str = None): |
| |
| prefix = gen_prefix + " " if gen_prefix else "" |
| n_samples = ( |
| num_fewshot + 1 |
| if self.config.fewshot_split == self.config.test_split |
| else num_fewshot |
| ) |
|
|
| |
| fewshotex = self.sample(n_samples) |
|
|
| |
| |
| selected_docs = [x for x in fewshotex if x != doc][:num_fewshot] |
|
|
| labeled_examples = "" |
| for doc in selected_docs: |
| doc_content = self.doc_to_text(doc) |
| doc_target = self.doc_to_target(doc) |
| if self.config.doc_to_choice is None or isinstance(doc_content, str): |
| labeled_examples += doc_content |
| else: |
| labeled_examples += self.doc_to_choice(doc)[doc_content] |
|
|
| if doc_target != "": |
| labeled_examples += self.target_delimiter |
| labeled_examples += prefix |
| labeled_examples += ( |
| str(doc_target[0]) |
| if isinstance(doc_target, list) |
| else doc_target |
| if self.config.doc_to_choice is None or isinstance(doc_target, str) |
| else str(self.doc_to_choice(doc)[doc_target]) |
| ) |
| labeled_examples += self.fewshot_delimiter |
|
|
| return labeled_examples |
|
|
| def get_chat_context( |
| self, |
| doc: dict, |
| num_fewshot: int, |
| fewshot_as_multiturn: bool = False, |
| gen_prefix: Optional[str] = None, |
| ): |
| |
| prefix = gen_prefix + " " if gen_prefix else "" |
| chat_history = [] |
| |
| n_samples = ( |
| num_fewshot + 1 |
| if self.config.fewshot_split == self.config.test_split |
| else num_fewshot |
| ) |
| |
| fewshotex = self.sample(n_samples) |
|
|
| |
| |
| selected_docs = [x for x in fewshotex if x != doc][:num_fewshot] |
|
|
| if fewshot_as_multiturn: |
| for doc in selected_docs: |
| doc_content = self.doc_to_text(doc) |
| doc_target = self.doc_to_target(doc) |
| chat_history.append( |
| { |
| "role": "user", |
| "content": doc_content |
| if self.config.doc_to_choice is None |
| or isinstance(doc_content, str) |
| else self.doc_to_choice(doc)[doc_content], |
| } |
| ) |
| chat_history.append( |
| { |
| "role": "assistant", |
| "content": prefix + str(doc_target[0]) |
| if isinstance(doc_target, list) |
| else prefix + doc_target |
| if self.config.doc_to_choice is None |
| or isinstance(doc_target, str) |
| else prefix + str(self.doc_to_choice(doc)[doc_target]), |
| } |
| ) |
| else: |
| |
| chat_history.append( |
| { |
| "role": "user", |
| "content": self.get_context( |
| doc, num_fewshot, gen_prefix=gen_prefix |
| ), |
| } |
| ) |
|
|
| return chat_history |
|
|
| def sample(self, n: int): |
| """ |
| Draw `n` samples from our fewshot docs. This method should be overridden by subclasses. |
| """ |
|
|
| return self.rnd.sample(self.docs, n) |
|
|
|
|
| class FirstNSampler(ContextSampler): |
| def sample(self, n: int) -> None: |
| """ |
| Draw the first `n` samples in order from the specified split. |
| Used for tasks with "canonical" ordered fewshot examples, such as MMLU and CMMLU. |
| """ |
| assert n <= len(self.docs), ( |
| f"Error: number of fewshot samples requested exceeds the {len(self.docs)} that are available." |
| ) |
| return self.docs[:n] |
|
|
|
|
| class BalancedSampler(ContextSampler): |
| def sample(self, n: int) -> None: |
| """ |
| TODO: this should return approximately class-balanced samples from our fewshot examples. |
| TODO: what order should they be in? maybe random? |
| """ |
|
|
| pass |
|
|
|
|
| class ManualSampler(ContextSampler): |
| def sample(self, n: int) -> None: |
| """ """ |
| pass |
|
|
|
|
| SAMPLER_REGISTRY = { |
| "default": ContextSampler, |
| "first_n": FirstNSampler, |
| } |
|
|
|
|
| def get_sampler(name: str): |
| try: |
| return SAMPLER_REGISTRY[name] |
| except KeyError: |
| raise ValueError( |
| f"Attempted to use contextsampler '{name}', but no sampling strategy for this name found! Supported model names: {', '.join(SAMPLER_REGISTRY.keys())}" |
| ) |
|
|