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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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from src.backend.manage_requests import ( |
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FAILED_STATUS, |
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FINISHED_STATUS, |
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PENDING_STATUS, |
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RUNNING_STATUS, |
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check_completed_evals, |
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get_eval_requests, |
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set_eval_request, |
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) |
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from src.backend.run_eval_suite_harness import run_evaluation |
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from src.backend.sort_queue import sort_models_by_priority |
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from src.envs import ( |
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API, |
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DEVICE, |
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EVAL_REQUESTS_PATH_BACKEND, |
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EVAL_RESULTS_PATH_BACKEND, |
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LIMIT, |
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NUM_FEWSHOT, |
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QUEUE_REPO, |
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RESULTS_REPO, |
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TASKS_HARNESS, |
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TOKEN, |
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) |
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from src.logging import setup_logger |
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logging.getLogger("openai").setLevel(logging.WARNING) |
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logger = setup_logger(__name__) |
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pp = pprint.PrettyPrinter(width=80) |
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snapshot_download( |
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repo_id=RESULTS_REPO, |
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revision="main", |
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local_dir=EVAL_RESULTS_PATH_BACKEND, |
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repo_type="dataset", |
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max_workers=60, |
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token=TOKEN, |
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) |
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snapshot_download( |
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repo_id=QUEUE_REPO, |
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revision="main", |
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local_dir=EVAL_REQUESTS_PATH_BACKEND, |
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repo_type="dataset", |
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max_workers=60, |
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token=TOKEN, |
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) |
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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( |
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job_status=current_pending_status, hf_repo=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH_BACKEND |
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) |
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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="auto", |
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device=DEVICE, |
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limit=LIMIT, |
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) |
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if __name__ == "__main__": |
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run_auto_eval() |
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