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import csv |
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import os |
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from datetime import datetime |
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from typing import Optional, Union |
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import gradio as gr |
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from huggingface_hub import HfApi, Repository |
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from export import convert |
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DATASET_REPO_URL = "https://huggingface.co/datasets/optimum/exporters" |
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DATA_FILENAME = "data.csv" |
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DATA_FILE = os.path.join("openvino", DATA_FILENAME) |
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HF_TOKEN = os.environ.get("HF_WRITE_TOKEN") |
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DATA_DIR = "exporters_data" |
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repo = None |
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if HF_TOKEN: |
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repo = Repository(local_dir=DATA_DIR, clone_from=DATASET_REPO_URL, token=HF_TOKEN) |
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def export(token: str, model_id: str, task: str) -> str: |
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if token == "" or model_id == "": |
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return """ |
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### Invalid input 🐞 |
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Please fill a token and model name. |
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""" |
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try: |
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api = HfApi(token=token) |
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error, commit_info = convert(api=api, model_id=model_id, task=task, force=False) |
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if error != "0": |
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return error |
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print("[commit_info]", commit_info) |
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if repo is not None: |
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repo.git_pull(rebase=True) |
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with open(os.path.join(DATA_DIR, DATA_FILE), "a") as csvfile: |
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writer = csv.DictWriter(csvfile, fieldnames=["model_id", "pr_url", "time"]) |
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writer.writerow( |
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{ |
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"model_id": model_id, |
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"pr_url": commit_info.pr_url, |
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"time": str(datetime.now()), |
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} |
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) |
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commit_url = repo.push_to_hub() |
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print("[dataset]", commit_url) |
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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})" |
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except Exception as e: |
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return f"#### Error: {e}" |
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TTILE_IMAGE = """ |
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<div |
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style=" |
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display: block; |
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margin-left: auto; |
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margin-right: auto; |
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width: 50%; |
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" |
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> |
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<img src="https://huggingface.co/spaces/echarlaix/openvino-export/resolve/main/header.png"/> |
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</div> |
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""" |
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TITLE = """ |
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<div |
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style=" |
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display: inline-flex; |
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align-items: center; |
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text-align: center; |
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max-width: 1400px; |
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gap: 0.8rem; |
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font-size: 2.2rem; |
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" |
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> |
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<h1 style="font-weight: 900; margin-bottom: 10px; margin-top: 10px;"> |
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Export your Transformers and Diffusers model to OpenVINO with 🤗 Optimum Intel (experimental) |
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</h1> |
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</div> |
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""" |
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DESCRIPTION = """ |
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This Space allows you to automatically export to the OpenVINO format various 🤗 Transformers and Diffusers PyTorch models hosted on the Hugging Face Hub. |
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Once exported, you will be able to load the resulting model using the [🤗 Optimum Intel](https://huggingface.co/docs/optimum/intel/inference). |
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To export your model, the steps are as following: |
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- Paste a read-access token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens). Read access is enough given that we will open a PR against the source repo. |
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- Input a model id from the Hub (for example: [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english)) |
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- Click "Export" |
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- That’s it! You’ll get feedback if it works or not, and if it worked, you’ll get the URL of the opened PR 🔥 |
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""" |
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with gr.Blocks() as demo: |
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gr.HTML(TTILE_IMAGE) |
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gr.HTML(TITLE) |
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with gr.Row(): |
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with gr.Column(scale=50): |
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gr.Markdown(DESCRIPTION) |
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with gr.Column(scale=50): |
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input_token = gr.Textbox( |
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max_lines=1, |
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label="Hugging Face token", |
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) |
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input_model = gr.Textbox( |
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max_lines=1, |
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label="Model name", |
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placeholder="distilbert-base-uncased-finetuned-sst-2-english", |
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) |
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input_task = gr.Textbox( |
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value="auto", |
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max_lines=1, |
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label='Task (can be left to "auto", will be automatically inferred)', |
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) |
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btn = gr.Button("Export") |
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output = gr.Markdown(label="Output") |
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btn.click( |
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fn=export, |
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inputs=[input_token, input_model, input_task], |
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outputs=output, |
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) |
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demo.launch() |
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