Spaces:
Running
Running
| import json | |
| import os | |
| from datetime import datetime, timezone | |
| from src.display.formatting import styled_error, styled_message, styled_warning | |
| from src.envs import API, EVAL_REQUESTS_PATH, TOKEN, QUEUE_REPO | |
| from src.submission.check_validity import ( | |
| already_submitted_models, | |
| check_model_card, | |
| get_model_size, | |
| is_model_on_hub, | |
| ) | |
| REQUESTED_MODELS = None | |
| USERS_TO_SUBMISSION_DATES = None | |
| def add_new_eval( | |
| model_name: str, | |
| preds_path: str, | |
| track: str, | |
| revision: str, | |
| ): | |
| global REQUESTED_MODELS | |
| global USERS_TO_SUBMISSION_DATES | |
| if not REQUESTED_MODELS: | |
| REQUESTED_MODELS, USERS_TO_SUBMISSION_DATES = already_submitted_models(EVAL_REQUESTS_PATH) | |
| user_name = "" | |
| model_path = model_name | |
| if "/" in model_name: | |
| user_name = model_name.split("/")[0] | |
| model_path = model_name.split("/")[1] | |
| current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ") | |
| if preds_path is None or preds_path == "": | |
| return styled_error("Please enter a URL where your predictions file can be downloaded.") | |
| if track is None: | |
| return styled_error("Please select a track.") | |
| # Does the model actually exist? | |
| if revision == "": | |
| revision = "main" | |
| # Is the model info correctly filled? | |
| try: | |
| model_info = API.model_info(repo_id=model_name, revision=revision) | |
| except Exception: | |
| return styled_error("Could not get your model information. Please fill it up properly.") | |
| modelcard_OK, error_msg = check_model_card(model_name) | |
| if not modelcard_OK: | |
| return styled_error(error_msg) | |
| # Seems good, creating the eval | |
| print("Adding new eval") | |
| eval_entry = { | |
| "model_name": model_name, | |
| "preds_path": preds_path, | |
| "track": track, | |
| "revision": revision, | |
| "status": "PENDING", | |
| "submitted_time": current_time, | |
| "private": False, | |
| } | |
| # Check for duplicate submission | |
| if f"{model_name}_{revision}_{track}" in REQUESTED_MODELS: | |
| return styled_warning("This model has been already submitted.") | |
| print("Creating eval file") | |
| OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}" | |
| os.makedirs(OUT_DIR, exist_ok=True) | |
| out_path = f"{OUT_DIR}/{model_path}_eval_request_False_{track}.json" | |
| with open(out_path, "w") as f: | |
| f.write(json.dumps(eval_entry)) | |
| print("Uploading eval file") | |
| API.upload_file( | |
| path_or_fileobj=out_path, | |
| path_in_repo=out_path.split("eval-queue/")[1], | |
| repo_id=QUEUE_REPO, | |
| repo_type="dataset", | |
| commit_message=f"Add {model_name} to eval queue", | |
| ) | |
| # Remove the local file | |
| os.remove(out_path) | |
| return styled_message( | |
| "Your request has been submitted to the evaluation queue!\nPlease wait for up to an hour for the model to show in the PENDING list." | |
| ) | |