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Benchmark Datasets - Dataset loaders for benchmark evaluation
Supports common evaluation datasets such as GSM8K, HumanEval, etc.
"""
from typing import List, Dict, Any, Optional, Callable
from datasets import load_dataset
def load_gsm8k(
split: str = "test",
limit: Optional[int] = None,
prompt_template: Optional[Callable[[str], str]] = None,
) -> List[Dict[str, Any]]:
"""
Load GSM8K dataset
Args:
split: Dataset split, default "test"
limit: Limit number of samples, None means all
prompt_template: Prompt template function that takes question string and returns full prompt
Returns:
List of dataset items, each containing 'prompt' and 'answer' fields
"""
dataset = load_dataset("gsm8k", "main", split=split)
if limit:
dataset = dataset[:limit]
results = []
for item in dataset:
question = item["question"]
answer = item["answer"]
if prompt_template:
prompt = prompt_template(question)
else:
# Default template
prompt = f"Question: {question}\nAnswer:"
results.append(
{
"prompt": prompt,
"answer": answer,
"question": question,
}
)
return results
def load_humaneval(
limit: Optional[int] = None,
prompt_template: Optional[Callable[[str], str]] = None,
) -> List[Dict[str, Any]]:
"""
Load HumanEval dataset
Args:
limit: Limit number of samples, None means all
prompt_template: Prompt template function that takes prompt string and returns full prompt
Returns:
List of dataset items, each containing 'prompt', 'test', 'entry_point' fields
"""
dataset = load_dataset("openai/humaneval", split="test")
if limit:
dataset = dataset[:limit]
results = []
for item in dataset:
prompt = item["prompt"]
test = item["test"]
entry_point = item["entry_point"]
if prompt_template:
full_prompt = prompt_template(prompt)
else:
full_prompt = prompt
results.append(
{
"prompt": full_prompt,
"original_prompt": prompt,
"test": test,
"entry_point": entry_point,
"task_id": item.get("task_id", ""),
}
)
return results
def load_benchmark_dataset(dataset_name: str, **kwargs) -> List[Dict[str, Any]]:
"""
Unified dataset loading interface
Args:
dataset_name: Dataset name, supports "gsm8k", "humaneval"
**kwargs: Arguments passed to the specific dataset loader
Returns:
List of dataset items
"""
loaders = {
"gsm8k": load_gsm8k,
"humaneval": load_humaneval,
}
if dataset_name not in loaders:
raise ValueError(f"Unknown dataset: {dataset_name}. Supported datasets: {list(loaders.keys())}")
return loaders[dataset_name](**kwargs)
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