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# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Utility that updates the metadata of the Diffusers library in the repository `huggingface/diffusers-metadata`.
Usage for an update (as used by the GitHub action `update_metadata`):
```bash
python utils/update_metadata.py
```
Script modified from:
https://github.com/huggingface/transformers/blob/main/utils/update_metadata.py
"""
import argparse
import os
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from diffusers.pipelines.auto_pipeline import (
AUTO_IMAGE2IMAGE_PIPELINES_MAPPING,
AUTO_INPAINT_PIPELINES_MAPPING,
AUTO_TEXT2IMAGE_PIPELINES_MAPPING,
)
PIPELINE_TAG_JSON = "pipeline_tags.json"
def get_supported_pipeline_table() -> dict:
"""
Generates a dictionary containing the supported auto classes for each pipeline type,
using the content of the auto modules.
"""
# All supported pipelines for automatic mapping.
all_supported_pipeline_classes = [
(class_name.__name__, "text-to-image", "AutoPipelineForText2Image")
for _, class_name in AUTO_TEXT2IMAGE_PIPELINES_MAPPING.items()
]
all_supported_pipeline_classes += [
(class_name.__name__, "image-to-image", "AutoPipelineForImage2Image")
for _, class_name in AUTO_IMAGE2IMAGE_PIPELINES_MAPPING.items()
]
all_supported_pipeline_classes += [
(class_name.__name__, "image-to-image", "AutoPipelineForInpainting")
for _, class_name in AUTO_INPAINT_PIPELINES_MAPPING.items()
]
all_supported_pipeline_classes = list(set(all_supported_pipeline_classes))
all_supported_pipeline_classes.sort(key=lambda x: x[0])
data = {}
data["pipeline_class"] = [sample[0] for sample in all_supported_pipeline_classes]
data["pipeline_tag"] = [sample[1] for sample in all_supported_pipeline_classes]
data["auto_class"] = [sample[2] for sample in all_supported_pipeline_classes]
return data
def update_metadata(commit_sha: str):
"""
Update the metadata for the Diffusers repo in `huggingface/diffusers-metadata`.
Args:
commit_sha (`str`): The commit SHA on Diffusers corresponding to this update.
"""
pipelines_table = get_supported_pipeline_table()
pipelines_table = pd.DataFrame(pipelines_table)
pipelines_dataset = Dataset.from_pandas(pipelines_table)
hub_pipeline_tags_json = hf_hub_download(
repo_id="huggingface/diffusers-metadata",
filename=PIPELINE_TAG_JSON,
repo_type="dataset",
)
with open(hub_pipeline_tags_json) as f:
hub_pipeline_tags_json = f.read()
with tempfile.TemporaryDirectory() as tmp_dir:
pipelines_dataset.to_json(os.path.join(tmp_dir, PIPELINE_TAG_JSON))
with open(os.path.join(tmp_dir, PIPELINE_TAG_JSON)) as f:
pipeline_tags_json = f.read()
hub_pipeline_tags_equal = hub_pipeline_tags_json == pipeline_tags_json
if hub_pipeline_tags_equal:
print("No updates, not pushing the metadata files.")
return
if commit_sha is not None:
commit_message = (
f"Update with commit {commit_sha}\n\nSee: "
f"https://github.com/huggingface/diffusers/commit/{commit_sha}"
)
else:
commit_message = "Update"
upload_folder(
repo_id="huggingface/diffusers-metadata",
folder_path=tmp_dir,
repo_type="dataset",
commit_message=commit_message,
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--commit_sha", default=None, type=str, help="The sha of the commit going with this update.")
args = parser.parse_args()
update_metadata(args.commit_sha)
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