adapt_trans_config.py

import argparse
import json
import os
import shutil
from tempfile import TemporaryDirectory
from typing import List, Optional

from huggingface_hub import (
    CommitInfo,
    CommitOperationAdd,
    Discussion,
    HfApi,
    hf_hub_download,
)
from huggingface_hub.file_download import repo_folder_name


class AlreadyExists(Exception):
    pass


def convert_single(model_id: str, folder: str) -> List["CommitOperationAdd"]:
    config_file_name = "generation_config.json"
    config_file = hf_hub_download(repo_id=model_id, filename=config_file_name)

    old_config_file = config_file

    new_config_file = os.path.join(folder, config_file)
    success = convert_file(old_config_file, new_config_file)
    if success:
        operations = [
            CommitOperationAdd(
                path_in_repo=config_file_name, path_or_fileobj=new_config_file
            )
        ]
        model_type = success
        return operations, model_type
    else:
        return False, False


def convert_file(
    old_config: str,
    new_config: str,
):
    with open(old_config, "r") as f:
        old_dict = json.load(f)

    old_dict["max_initial_timestamp_index"] = 50
    old_dict["prev_sot_token_id"] = old_dict["suppress_tokens"][-2]

    with open(new_config, "w") as f:
        json_str = json.dumps(old_dict, indent=2, sort_keys=True) + "\n"
        f.write(json_str)

    return "Whisper"


def previous_pr(api: "HfApi", model_id: str, pr_title: str) -> Optional["Discussion"]:
    try:
        discussions = api.get_repo_discussions(repo_id=model_id)
    except Exception:
        return None
    for discussion in discussions:
        if (
            discussion.status == "open"
            and discussion.is_pull_request
            and discussion.title == pr_title
        ):
            return discussion


def convert(api: "HfApi", model_id: str, force: bool = False) -> Optional["CommitInfo"]:
    pr_title = "Correct long-form generation config parameters 'max_initial_timestamp_index' and 'prev_sot_token_id'."
    info = api.model_info(model_id)
    filenames = set(s.rfilename for s in info.siblings)

    if "generation_config.json" not in filenames:
        print(f"Model: {model_id} has no generation_config.json file to change")
        return

    with TemporaryDirectory() as d:
        folder = os.path.join(d, repo_folder_name(repo_id=model_id, repo_type="models"))
        os.makedirs(folder)
        new_pr = None
        try:
            operations = None
            pr = previous_pr(api, model_id, pr_title)
            if pr is not None and not force:
                url = f"https://huggingface.co/{model_id}/discussions/{pr.num}"
                new_pr = pr
                raise AlreadyExists(
                    f"Model {model_id} already has an open PR check out {url}"
                )
            else:
                operations, model_type = convert_single(model_id, folder)

            if operations:
                pr_title = pr_title.format(model_type)
                contributor = model_id.split("/")[0]
                pr_description = (
                    f"Hey {contributor} 👋, \n\n Your model repository seems to contain outdated generation config parameters, such as 'max_initial_timestamp_index' and is missing the 'prev_sot_token_id' parameter. "
                    "These parameters need to be updated to correctly handle long-form generation as stated in  as part of https://github.com/huggingface/transformers/pull/27658. "
                    "This PR makes sure that everything is up to date and can be safely merged. \n\n Best, the Transformers team."
                )
                new_pr = api.create_commit(
                    repo_id=model_id,
                    operations=operations,
                    commit_message=pr_title,
                    commit_description=pr_description,
                    create_pr=True,
                )
                print(f"Pr created at {new_pr.pr_url}")
            else:
                print(f"No files to convert for {model_id}")
        finally:
            shutil.rmtree(folder)
        return new_pr


if __name__ == "__main__":
    DESCRIPTION = """
    Simple utility tool to convert automatically some weights on the hub to `safetensors` format.
    It is PyTorch exclusive for now.
    It works by downloading the weights (PT), converting them locally, and uploading them back
    as a PR on the hub.
    """
    parser = argparse.ArgumentParser(description=DESCRIPTION)
    parser.add_argument(
        "model_id",
        type=str,
        help="The name of the model on the hub to convert. E.g. `gpt2` or `facebook/wav2vec2-base-960h`",
    )
    parser.add_argument(
        "--force",
        action="store_true",
        help="Create the PR even if it already exists of if the model was already converted.",
    )
    args = parser.parse_args()
    model_id = args.model_id
    api = HfApi()
    convert(api, model_id, force=args.force)