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| import csv | |
| import os | |
| from datetime import datetime | |
| from typing import Optional, Union | |
| import gradio as gr | |
| from huggingface_hub import HfApi, Repository | |
| from export import convert | |
| from gradio_huggingfacehub_search import HuggingfaceHubSearch | |
| DATASET_REPO_URL = "https://huggingface.co/datasets/optimum/exporters" | |
| DATA_FILENAME = "data.csv" | |
| DATA_FILE = os.path.join("openvino", DATA_FILENAME) | |
| HF_TOKEN = os.environ.get("HF_WRITE_TOKEN") | |
| DATA_DIR = "exporters_data" | |
| repo = None | |
| if HF_TOKEN: | |
| repo = Repository(local_dir=DATA_DIR, clone_from=DATASET_REPO_URL, token=HF_TOKEN) | |
| def export(model_id: str, token: str, task: str = "auto") -> str: | |
| if model_id == "" or token == "": | |
| return """ | |
| ### Invalid input 🐞 | |
| Please fill a token and model name. | |
| """ | |
| try: | |
| api = HfApi(token=token) | |
| error, commit_info = convert(api=api, model_id=model_id, task=task, force=False) | |
| if error != "0": | |
| return error | |
| print("[commit_info]", commit_info) | |
| # save in a private dataset | |
| if repo is not None: | |
| repo.git_pull(rebase=True) | |
| with open(os.path.join(DATA_DIR, DATA_FILE), "a") as csvfile: | |
| writer = csv.DictWriter(csvfile, fieldnames=["model_id", "pr_url", "time"]) | |
| writer.writerow( | |
| { | |
| "model_id": model_id, | |
| "pr_url": commit_info.pr_url, | |
| "time": str(datetime.now()), | |
| } | |
| ) | |
| commit_url = repo.push_to_hub() | |
| print("[dataset]", commit_url) | |
| return f"#### Success 🔥 Yay! This model was successfully exported and a PR was open using your token, here: [{commit_info.pr_url}]({commit_info.pr_url})" | |
| except Exception as e: | |
| return f"#### Error: {e}" | |
| TTILE_IMAGE = """ | |
| <div | |
| style=" | |
| display: block; | |
| margin-left: auto; | |
| margin-right: auto; | |
| width: 50%; | |
| " | |
| > | |
| <img src="https://huggingface.co/spaces/echarlaix/openvino-export/resolve/main/header.png"/> | |
| </div> | |
| """ | |
| TITLE = """ | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| text-align: center; | |
| max-width: 1400px; | |
| gap: 0.8rem; | |
| font-size: 2.2rem; | |
| " | |
| > | |
| <h1 style="text-align:center; font-weight: 1200"> | |
| Export your model to OpenVINO | |
| </h1> | |
| </div> | |
| """ | |
| DESCRIPTION = """ | |
| This Space uses [Optimum Intel](https://huggingface.co/docs/optimum/intel/inference) to automatically export your model to the OpenVINO format. | |
| After the model conversion, we will open a PR against the source repo to add the resulting model. | |
| To export your model you need: | |
| - A Model ID from the Hub | |
| - A read-access token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens). | |
| That's it ! 🔥 | |
| """ | |
| interface = gr.Interface( | |
| fn=export, | |
| inputs=[ | |
| HuggingfaceHubSearch( | |
| label="Hub Model ID", | |
| placeholder="Search for model id on Huggingface", | |
| search_type="model", | |
| ), | |
| gr.Textbox( | |
| max_lines=1, | |
| label="Hugging Face token", | |
| ), | |
| gr.Textbox( | |
| label="Task", | |
| info="Can be left to auto, will be automatically inferred", | |
| placeholder="auto", | |
| max_lines=1, | |
| ), | |
| ], | |
| outputs=[ | |
| gr.Markdown(label="output"), | |
| ], | |
| submit_btn=gr.Button("Export"), | |
| title=TITLE, | |
| description=DESCRIPTION, | |
| ) | |
| with gr.Blocks() as demo: | |
| # gr.HTML(TTILE_IMAGE) | |
| # gr.HTML(TITLE) | |
| interface.render() | |
| demo.launch() | |