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import logging |
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import pprint |
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from huggingface_hub import snapshot_download |
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logging.getLogger("openai").setLevel(logging.WARNING) |
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from backend.run_eval_suite_harness import run_evaluation |
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from src.backend.manage_requests import check_completed_evals, get_eval_requests, set_eval_request |
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from src.backend.sort_queue import sort_models_by_priority |
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from src.envs import QUEUE_REPO, EVAL_REQUESTS_PATH_BACKEND, RESULTS_REPO, EVAL_RESULTS_PATH_BACKEND, DEVICE, API, LIMIT, TOKEN |
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from src.about import Tasks, NUM_FEWSHOT |
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from src.logging import setup_logger |
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TASKS_HARNESS = [task.value.benchmark for task in Tasks] |
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logger = setup_logger(__name__) |
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pp = pprint.PrettyPrinter(width=80) |
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PENDING_STATUS = "PENDING" |
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RUNNING_STATUS = "RUNNING" |
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FINISHED_STATUS = "FINISHED" |
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FAILED_STATUS = "FAILED" |
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snapshot_download(repo_id=RESULTS_REPO, revision="main", local_dir=EVAL_RESULTS_PATH_BACKEND, repo_type="dataset", max_workers=60, token=TOKEN) |
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snapshot_download(repo_id=QUEUE_REPO, revision="main", local_dir=EVAL_REQUESTS_PATH_BACKEND, repo_type="dataset", max_workers=60, token=TOKEN) |
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def run_auto_eval(): |
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current_pending_status = [PENDING_STATUS] |
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check_completed_evals( |
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api=API, |
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checked_status=RUNNING_STATUS, |
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completed_status=FINISHED_STATUS, |
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failed_status=FAILED_STATUS, |
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hf_repo=QUEUE_REPO, |
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local_dir=EVAL_REQUESTS_PATH_BACKEND, |
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hf_repo_results=RESULTS_REPO, |
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local_dir_results=EVAL_RESULTS_PATH_BACKEND |
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) |
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eval_requests = get_eval_requests(job_status=current_pending_status, hf_repo=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH_BACKEND) |
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eval_requests = sort_models_by_priority(api=API, models=eval_requests) |
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print(f"Found {len(eval_requests)} {','.join(current_pending_status)} eval requests") |
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if len(eval_requests) == 0: |
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return |
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eval_request = eval_requests[0] |
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logger.info(pp.pformat(eval_request)) |
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set_eval_request( |
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api=API, |
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eval_request=eval_request, |
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set_to_status=RUNNING_STATUS, |
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hf_repo=QUEUE_REPO, |
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local_dir=EVAL_REQUESTS_PATH_BACKEND, |
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) |
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run_evaluation( |
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eval_request=eval_request, |
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task_names=TASKS_HARNESS, |
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num_fewshot=NUM_FEWSHOT, |
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local_dir=EVAL_RESULTS_PATH_BACKEND, |
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results_repo=RESULTS_REPO, |
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batch_size=1, |
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device=DEVICE, |
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no_cache=True, |
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limit=LIMIT |
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) |
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if __name__ == "__main__": |
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run_auto_eval() |
