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6b17493
1
Parent(s):
6b7e2c1
More efficient telemetry uploading (#157)
Browse files- Zip files before uploading (be16637857c14da2cd7feaf60d9dea9e85da7e42)
- app.py +56 -29
- requirements.txt +2 -0
app.py
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@@ -6,6 +6,9 @@ import json
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import os
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import random
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import tempfile
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import gradio as gr
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import torch
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@@ -105,15 +108,18 @@ def upload_stage1_result(stage1_param_path: str, stage1_result_path: str,
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if not UPLOAD_REPO_ID:
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return
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try:
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except Exception as e:
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print(e)
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@@ -140,18 +146,20 @@ def upload_stage2_info(stage1_param_file_hash_name: str,
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param_file.write(json.dumps(stage2_params))
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stage2_param_file_hash_name = get_param_file_hash_name(param_file.name)
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save_name = f'{stage1_param_file_hash_name}_{stage2_param_file_hash_name}'
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try:
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if UPLOAD_RESULT_IMAGE:
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except Exception as e:
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print(e)
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@@ -188,17 +196,16 @@ def upload_stage2_3_info(stage1_param_file_hash_name: str,
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save_name = f'{stage1_param_file_hash_name}_{stage2_3_param_file_hash_name}'
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try:
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if UPLOAD_RESULT_IMAGE:
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repo_type='dataset')
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except Exception as e:
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print(e)
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@@ -221,6 +228,21 @@ def show_gallery_view() -> tuple[dict, dict]:
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def show_upscaled_view() -> tuple[dict, dict]:
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return _update_result_view(False)
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examples = [
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'high quality dslr photo, a photo product of a lemon inspired by natural and organic materials, wooden accents, intricately decorated with glowing vines of led lights, inspired by baroque luxury',
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@@ -669,5 +691,10 @@ with gr.Blocks(css='style.css') as demo:
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],
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queue=False,
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)
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demo.queue(api_open=False, max_size=MAX_QUEUE_SIZE).launch(debug=DEBUG)
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import os
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import random
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import tempfile
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import shortuuid
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from apscheduler.schedulers.background import BackgroundScheduler
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import shutil
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import gradio as gr
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import torch
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if not UPLOAD_REPO_ID:
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return
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try:
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folder_params = "tmp/results/stage1_params"
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folder_results = "tmp/results/stage1_results"
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path_params = f"{folder_params}/{save_name}.json"
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path_results = f"{folder_results}/{save_name}.pth"
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os.makedirs(folder_params, exist_ok=True)
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os.makedirs(folder_results, exist_ok=True)
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shutil.copy(stage1_param_path, path_params)
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shutil.copy(stage1_result_path, path_results)
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except Exception as e:
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print(e)
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param_file.write(json.dumps(stage2_params))
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stage2_param_file_hash_name = get_param_file_hash_name(param_file.name)
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save_name = f'{stage1_param_file_hash_name}_{stage2_param_file_hash_name}'
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try:
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folder_params = "tmp/results/stage2_params"
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os.makedirs(folder_params, exist_ok=True)
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path_params = f"{folder_params}/{save_name}.json"
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shutil.copy(param_file.name, path_params)
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if UPLOAD_RESULT_IMAGE:
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folder_results = "tmp/results/stage2_results"
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os.makedirs(folder_results, exist_ok=True)
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path_results = f"{folder_results}/{save_name}.png"
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shutil.copy(stage2_output_path, path_results)
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except Exception as e:
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print(e)
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save_name = f'{stage1_param_file_hash_name}_{stage2_3_param_file_hash_name}'
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try:
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folder_params = "tmp/results/stage2_3_params"
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os.makedirs(folder_params, exist_ok=True)
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path_params = f"{folder_params}/{save_name}.json"
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shutil.copy(param_file.name, path_params)
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if UPLOAD_RESULT_IMAGE:
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folder_results = "tmp/results/stage2_3_results"
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os.makedirs(folder_results, exist_ok=True)
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path_results = f"{folder_results}/{save_name}.png"
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shutil.copy(stage2_3_output_path, path_results)
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except Exception as e:
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print(e)
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def show_upscaled_view() -> tuple[dict, dict]:
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return _update_result_view(False)
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def upload_files():
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"""Zips files and uploads to dataset. Local data is deleted
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"""
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if os.path.exists("tmp/results") and os.path.isdir("tmp/results"):
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try:
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shutil.make_archive("tmp/results", 'zip', "tmp/results")
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hf_api.upload_file(
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path_or_fileobj="tmp/results.zip",
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path_in_repo=f"results_{shortuuid.uuid()}.zip",
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repo_id=UPLOAD_REPO_ID,
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repo_type="dataset",
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)
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shutil.rmtree("tmp/results")
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except Exception as e:
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print(e)
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examples = [
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'high quality dslr photo, a photo product of a lemon inspired by natural and organic materials, wooden accents, intricately decorated with glowing vines of led lights, inspired by baroque luxury',
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],
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queue=False,
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)
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if UPLOAD_REPO_ID:
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scheduler = BackgroundScheduler()
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scheduler.add_job(func=upload_files, trigger="interval", seconds=60*5)
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scheduler.start()
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demo.queue(api_open=False, max_size=MAX_QUEUE_SIZE).launch(debug=DEBUG)
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requirements.txt
CHANGED
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@@ -12,3 +12,5 @@ sentencepiece==0.1.98
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tokenizers==0.13.3
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tqdm==4.65.0
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transformers==4.28.1
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tokenizers==0.13.3
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tqdm==4.65.0
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transformers==4.28.1
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shortuuid==1.0.11
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apscheduler==3.10.1
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