up

adapt_trans_config.py

@@ -0,0 +1,142 @@
+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)

all_ids.txt

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+openai/whisper-large-v3
+openai/whisper-large-v2
+brunoqgalvao/whisper-small-pt-br
+openai/whisper-base.en
+openai/whisper-tiny.en
+openai/whisper-small
+distil-whisper/distil-medium.en
+openai/whisper-base
+openai/whisper-tiny
+openai/whisper-small.en
+openai/whisper-medium
+openai/whisper-large
+MU-NLPC/whisper-small-audio-captioning
+distil-whisper/distil-large-v2
+hf-internal-testing/tiny-random-WhisperForConditionalGeneration
+openai/whisper-medium.en
+tarteel-ai/whisper-base-ar-quran
+distil-whisper/distil-small.en
+sawradip/bengali-whisper-medium-tugstugi
+vasista22/whisper-gujarati-medium
+vumichien/whisper-medium-jp
+sanchit-gandhi/whisper-medium-fleurs-lang-id
+vasista22/whisper-hindi-large-v2
+simonl0909/whisper-large-v2-cantonese
+bofenghuang/whisper-small-cv11-french
+shhossain/whisper-tiny-bn-emo
+Subhaka/whisper-small-Sinhala-Fine_Tune
+biodatlab/whisper-th-medium-combined
+primeline/whisper-large-v3-german
+UnlikelyAI/whisper-tiny-demo

download_1.py

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+#!/usr/bin/env python3
+from diffusers import DiffusionPipeline
+
+pipeline = DiffusionPipeline.from_pretrained(
+    "hf-internal-testing/diffusers-stable-diffusion-tiny-all"
+)

mass_config_trans_adapt.sh

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+#!/usr/bin/env bash
+while read p; do
+	echo "-------------------------------"
+	echo "Attempting to open PR for $p"
+	python adapt_trans_config.py $p
+done <all_ids.txt