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import ast
import os
from typing import Dict
from lm_eval import utils
from lm_eval.utils import eval_logger
# Prompt library.
# Stores prompts in a dictionary indexed by 2 levels:
# prompt category name, and prompt name.
# This allows us to access prompts
PROMPT_REGISTRY: Dict[str, Dict[str, str]] = {
"qa-basic": {
"question-newline-answer": "Question: {{question}}\nAnswer:",
"q-newline-a": "Q: {{question}}\nA:",
},
}
def get_prompt(prompt_id: str, dataset_name: str = None, subset_name: str = None):
# unpack prompt name
category_name, prompt_name = prompt_id.split(":")
if subset_name is None:
dataset_full_name = dataset_name
else:
dataset_full_name = f"{dataset_name}-{subset_name}"
eval_logger.info(f"Loading prompt from {category_name} for {dataset_full_name}")
if category_name == "promptsource":
try:
from promptsource.templates import DatasetTemplates
except ModuleNotFoundError:
raise Exception(
"Tried to load a Promptsource template, but promptsource is not installed ",
"please install promptsource via pip install lm-eval[promptsource] or pip install -e .[promptsource]",
)
try:
if subset_name is None:
prompts = DatasetTemplates(dataset_name=dataset_name)
else:
prompts = DatasetTemplates(
dataset_name=dataset_name, subset_name=subset_name
)
except Exception:
raise ValueError(f"{dataset_name} and {subset_name} not found")
if prompt_name in prompts.all_template_names:
return prompts[prompt_name]
else:
raise ValueError(
f"{prompt_name} not in prompt list {prompts.all_template_names}"
)
elif ".yaml" in category_name:
import yaml
with open(category_name, "rb") as file:
prompt_yaml_file = yaml.full_load(file)
prompt_string = prompt_yaml_file["prompts"][prompt_name]
return PromptString(prompt_string)
else:
try:
return PROMPT_REGISTRY[category_name][prompt_name]
except Exception:
raise ValueError(
f"expected only a single `:` as separator between \
prompt category and name, but got `{prompt_id}` instead"
)
def load_prompt_list(
use_prompt: str, dataset_name=None, subset_name=None, yaml_path=None, **kwargs
):
category_name, prompt_name = use_prompt.split(":")
if category_name == "promptsource":
from promptsource.templates import DatasetTemplates
if subset_name is None:
prompts = DatasetTemplates(dataset_name=dataset_name)
else:
prompts = DatasetTemplates(
dataset_name=dataset_name, subset_name=subset_name
)
prompt_list = utils.pattern_match(prompt_name, prompts.all_template_names)
elif ".yaml" in category_name:
import yaml
if yaml_path is not None:
category_name = os.path.realpath(os.path.join(yaml_path, category_name))
with open(category_name, "rb") as file:
prompt_yaml_file = yaml.full_load(file)
prompt_list = utils.pattern_match(
prompt_name, prompt_yaml_file["prompts"].keys()
)
# category_name, *prompt_name = use_prompt.split(":")
# TODO allow to multiple prompt naming
# if len(prompt_name) > 1:
# prompt_list = []
# for prompt in prompt_name:
# prompt_list.append(utils.pattern_match(prompt_name, prompts.all_template_names))
# else:
# prompt_list = utils.pattern_match(prompt_name, prompts.all_template_names)
return [":".join([category_name, prompt]) for prompt in prompt_list]
class PromptString:
def __init__(self, prompt_string):
self.prompt_string = prompt_string
def apply(self, doc):
doc_to_text = self.prompt_string["doc_to_text"]
doc_to_target = self.prompt_string["doc_to_target"]
# TODO need a way to process doc_to_choice
if "doc_to_choice" in self.prompt_string:
raise Exception("Not yet implemented to accept doc_to_choice")
text_string = utils.apply_template(doc_to_text, doc)
target_string = utils.apply_template(doc_to_target, doc)
return [text_string, target_string]
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