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"""
Frontier-CS: Evaluation framework for frontier CS problems.
Usage:
from frontier_cs import FrontierCSEvaluator
evaluator = FrontierCSEvaluator()
# Algorithmic problems
score = evaluator.evaluate("algorithmic", problem_id=1, code=cpp_code)
# Research problems (local Docker)
score = evaluator.evaluate("research", problem_id="flash_attn", code=py_code)
# Research problems (SkyPilot cloud)
score = evaluator.evaluate("research", problem_id="flash_attn", code=py_code,
backend="skypilot")
# Batch evaluation with incremental progress
from frontier_cs.batch import BatchEvaluator
batch = BatchEvaluator(results_dir="results/gpt5")
batch.evaluate_model("gpt-5", problems=["flash_attn", "cross_entropy"])
# Batch evaluation with bucket storage (for SkyPilot)
batch = BatchEvaluator(
results_dir="results/gpt5",
backend="skypilot",
bucket_url="s3://my-bucket/frontier-results",
)
batch.# Use batch.scan_solutions_dir() or evaluate_pairs()
"""
from .evaluator import FrontierCSEvaluator
from .config import RuntimeConfig, ResourcesConfig, DockerConfig, ProblemConfig
from .runner import EvaluationResult
__all__ = [
"FrontierCSEvaluator",
"RuntimeConfig",
"ResourcesConfig",
"DockerConfig",
"ProblemConfig",
"EvaluationResult",
]
__version__ = "0.1.0"
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