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on
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Running
on
T4
| # https://huggingface.co/yuntian-deng/latex2im_ss_finetunegptneo | |
| import gradio as gr | |
| import numpy as np | |
| import requests | |
| import base64 | |
| import os | |
| from datetime import datetime | |
| from pytz import timezone | |
| tz = timezone('EST') | |
| API_ENDPOINT = os.getenv('API_ENDPOINT') | |
| API_KEY = os.getenv('API_KEY') | |
| title = "<h1><center>Markup-to-Image Diffusion Models with Scheduled Sampling</center></h1>" | |
| authors = "<center>Yuntian Deng, Noriyuki Kojima, Alexander M. Rush</center>" | |
| info = '<center><a href="https://openreview.net/pdf?id=81VJDmOE2ol">Paper</a> <a href="https://github.com/da03/markup2im">Code</a></center>' | |
| with gr.Blocks() as demo: | |
| gr.Markdown(title) | |
| gr.Markdown(authors) | |
| gr.Markdown(info) | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| textbox = gr.Textbox(label=r'Type LaTeX formula below and click "Generate"', lines=1, max_lines=1, placeholder='Type LaTeX formula here and click "Generate"', value=r'\sum_{t=1}^T\E_{y_t \sim {\tilde P(y_t| y_0)}} \left\| \frac{y_t - \sqrt{\bar{\alpha}_t}y_0}{\sqrt{1-\bar{\alpha}_t}} - \epsilon_\theta(y_t, t)\right\|^2.') | |
| submit_btn = gr.Button("Generate", elem_id="btn") | |
| with gr.Column(scale=3): | |
| slider = gr.Slider(0, 1000, value=0, label='step (out of 1000)') | |
| image = gr.Image(label="Rendered Image", show_label=False, elem_id="image") | |
| inputs = [textbox] | |
| outputs = [slider, image, submit_btn] | |
| def infer(formula): | |
| current_time = datetime.now(tz) | |
| print (current_time, formula) | |
| data = {'formula': formula, 'api_key': API_KEY} | |
| try: | |
| with requests.post(url=API_ENDPOINT, data=data, timeout=600, stream=True) as r: | |
| i = 0 | |
| for line in r.iter_lines(): | |
| response = line.decode('ascii').strip() | |
| r = base64.decodebytes(response.encode('ascii')) | |
| q = np.frombuffer(r, dtype=np.float32).reshape((64, 320, 3)) | |
| i += 1 | |
| yield i, q, submit_btn.update(visible=False) | |
| yield i, q, submit_btn.update(visible=True) | |
| except Exception as e: | |
| yield 1000, 255*np.ones((64, 320, 3)), submit_btn.update(visible=True) | |
| submit_btn.click(fn=infer, inputs=inputs, outputs=outputs) | |
| demo.queue(concurrency_count=20, max_size=200).launch(enable_queue=True) | |