Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
mrfakename
commited on
Commit
β’
09cd5ce
1
Parent(s):
b72e390
2x speedup?
Browse files
app.py
CHANGED
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import gradio as gr
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import random
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import os
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import shutil
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import pandas as pd
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import sqlite3
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from datasets import load_dataset
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import threading
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import time
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import uuid
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from pathlib import Path
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from huggingface_hub import CommitScheduler, delete_file, hf_hub_download
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from gradio_client import Client
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@@ -475,6 +469,39 @@ with gr.Blocks() as leaderboard:
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# bothgood.click(both_good, outputs=outputs, inputs=[model1, model2, useridstate])
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# vote.load(reload, outputs=[aud1, aud2, model1, model2])
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def synthandreturn(text):
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text = text.strip()
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if len(text) > MAX_SAMPLE_TXT_LENGTH:
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@@ -489,30 +516,31 @@ def synthandreturn(text):
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mdl1, mdl2 = random.sample(list(AVAILABLE_MODELS.keys()), 2)
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log_text(text)
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print("[debug] Using", mdl1, mdl2)
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return (
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)
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def randomsent():
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return random.choice(sents), 'π²'
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def clear_stuff():
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import gradio as gr
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import pandas as pd
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from datasets import load_dataset
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import threading, time, uuid, sqlite3, shutil, os, random, asyncio
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from pathlib import Path
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from huggingface_hub import CommitScheduler, delete_file, hf_hub_download
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from gradio_client import Client
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# bothgood.click(both_good, outputs=outputs, inputs=[model1, model2, useridstate])
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# vote.load(reload, outputs=[aud1, aud2, model1, model2])
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############
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# 2x speedup (hopefully)
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############
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async def predict_async(text, model, api_name):
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return await router.predict(text, AVAILABLE_MODELS[model], api_name=api_name)
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async def predict_both_concurrently(text, mdl1, mdl2):
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task1 = predict_async(text, mdl1, "/synthesize")
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task2 = predict_async(text, mdl2, "/synthesize")
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results = await asyncio.gather(task1, task2)
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return results
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############
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# 2x speedup (hopefully)
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############
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async def process_predictions(text, mdl1, mdl2):
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aud1, aud2 = await predict_both_concurrently(text, mdl1, mdl2)
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return (
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text,
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"Synthesize",
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gr.update(visible=True),
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mdl1,
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mdl2,
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gr.update(visible=True, value=aud1),
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gr.update(visible=True, value=aud2),
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gr.update(visible=True, interactive=True),
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gr.update(visible=True, interactive=True),
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gr.update(visible=False),
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gr.update(visible=False),
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gr.update(visible=False),
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)
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def synthandreturn(text):
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text = text.strip()
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if len(text) > MAX_SAMPLE_TXT_LENGTH:
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mdl1, mdl2 = random.sample(list(AVAILABLE_MODELS.keys()), 2)
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log_text(text)
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print("[debug] Using", mdl1, mdl2)
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return asyncio.run(process_predictions(text, mdl1, mdl2))
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# return (
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# text,
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# "Synthesize",
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# gr.update(visible=True), # r2
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# mdl1, # model1
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# mdl2, # model2
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# # 'Vote to reveal model A', # prevmodel1
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# gr.update(visible=True, value=router.predict(
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# text,
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# AVAILABLE_MODELS[mdl1],
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# api_name="/synthesize"
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# )), # aud1
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# # 'Vote to reveal model B', # prevmodel2
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# gr.update(visible=True, value=router.predict(
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# text,
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# AVAILABLE_MODELS[mdl2],
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# api_name="/synthesize"
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# )), # aud2
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# gr.update(visible=True, interactive=True),
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# gr.update(visible=True, interactive=True),
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# gr.update(visible=False),
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# gr.update(visible=False),
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# gr.update(visible=False), #nxt round btn
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# )
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def randomsent():
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return random.choice(sents), 'π²'
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def clear_stuff():
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