Spaces:
Runtime error
Runtime error
File size: 9,641 Bytes
5325fcc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""
To run this script, from the root of the repo. Make sure to have Flask installed
FLASK_DEBUG=1 FLASK_APP=scripts.mos flask run -p 4567
# or if you have gunicorn
gunicorn -w 4 -b 127.0.0.1:8895 -t 120 'scripts.mos:app' --access-logfile -
"""
from collections import defaultdict
from functools import wraps
from hashlib import sha1
import json
import math
from pathlib import Path
import random
import typing as tp
from flask import Flask, redirect, render_template, request, session, url_for
from audiocraft import train
from audiocraft.utils.samples.manager import get_samples_for_xps
SAMPLES_PER_PAGE = 8
MAX_RATING = 5
storage = Path(train.main.dora.dir / 'mos_storage')
storage.mkdir(exist_ok=True)
surveys = storage / 'surveys'
surveys.mkdir(exist_ok=True)
magma_root = Path(train.__file__).parent.parent
app = Flask('mos', static_folder=str(magma_root / 'scripts/static'),
template_folder=str(magma_root / 'scripts/templates'))
app.secret_key = b'audiocraft makes the best songs'
def normalize_path(path: Path):
"""Just to make path a bit nicer, make them relative to the Dora root dir.
"""
path = path.resolve()
dora_dir = train.main.dora.dir.resolve() / 'xps'
return path.relative_to(dora_dir)
def get_full_path(normalized_path: Path):
"""Revert `normalize_path`.
"""
return train.main.dora.dir.resolve() / 'xps' / normalized_path
def get_signature(xps: tp.List[str]):
"""Return a signature for a list of XP signatures.
"""
return sha1(json.dumps(xps).encode()).hexdigest()[:10]
def ensure_logged(func):
"""Ensure user is logged in.
"""
@wraps(func)
def _wrapped(*args, **kwargs):
user = session.get('user')
if user is None:
return redirect(url_for('login', redirect_to=request.url))
return func(*args, **kwargs)
return _wrapped
@app.route('/login', methods=['GET', 'POST'])
def login():
"""Login user if not already, then redirect.
"""
user = session.get('user')
if user is None:
error = None
if request.method == 'POST':
user = request.form['user']
if not user:
error = 'User cannot be empty'
if user is None or error:
return render_template('login.html', error=error)
assert user
session['user'] = user
redirect_to = request.args.get('redirect_to')
if redirect_to is None:
redirect_to = url_for('index')
return redirect(redirect_to)
@app.route('/', methods=['GET', 'POST'])
@ensure_logged
def index():
"""Offer to create a new study.
"""
errors = []
if request.method == 'POST':
xps_or_grids = [part.strip() for part in request.form['xps'].split()]
xps = set()
for xp_or_grid in xps_or_grids:
xp_path = train.main.dora.dir / 'xps' / xp_or_grid
if xp_path.exists():
xps.add(xp_or_grid)
continue
grid_path = train.main.dora.dir / 'grids' / xp_or_grid
if grid_path.exists():
for child in grid_path.iterdir():
if child.is_symlink():
xps.add(child.name)
continue
errors.append(f'{xp_or_grid} is neither an XP nor a grid!')
assert xps or errors
blind = 'true' if request.form.get('blind') == 'on' else 'false'
xps = list(xps)
if not errors:
signature = get_signature(xps)
manifest = {
'xps': xps,
}
survey_path = surveys / signature
survey_path.mkdir(exist_ok=True)
with open(survey_path / 'manifest.json', 'w') as f:
json.dump(manifest, f, indent=2)
return redirect(url_for('survey', blind=blind, signature=signature))
return render_template('index.html', errors=errors)
@app.route('/survey/<signature>', methods=['GET', 'POST'])
@ensure_logged
def survey(signature):
success = request.args.get('success', False)
seed = int(request.args.get('seed', 4321))
blind = request.args.get('blind', 'false') in ['true', 'on', 'True']
exclude_prompted = request.args.get('exclude_prompted', 'false') in ['true', 'on', 'True']
exclude_unprompted = request.args.get('exclude_unprompted', 'false') in ['true', 'on', 'True']
max_epoch = int(request.args.get('max_epoch', '-1'))
survey_path = surveys / signature
assert survey_path.exists(), survey_path
user = session['user']
result_folder = survey_path / 'results'
result_folder.mkdir(exist_ok=True)
result_file = result_folder / f'{user}_{seed}.json'
with open(survey_path / 'manifest.json') as f:
manifest = json.load(f)
xps = [train.main.get_xp_from_sig(xp) for xp in manifest['xps']]
names, ref_name = train.main.get_names(xps)
samples_kwargs = {
'exclude_prompted': exclude_prompted,
'exclude_unprompted': exclude_unprompted,
'max_epoch': max_epoch,
}
matched_samples = get_samples_for_xps(xps, epoch=-1, **samples_kwargs) # fetch latest epoch
models_by_id = {
id: [{
'xp': xps[idx],
'xp_name': names[idx],
'model_id': f'{xps[idx].sig}-{sample.id}',
'sample': sample,
'is_prompted': sample.prompt is not None,
'errors': [],
} for idx, sample in enumerate(samples)]
for id, samples in matched_samples.items()
}
experiments = [
{'xp': xp, 'name': names[idx], 'epoch': list(matched_samples.values())[0][idx].epoch}
for idx, xp in enumerate(xps)
]
keys = list(matched_samples.keys())
keys.sort()
rng = random.Random(seed)
rng.shuffle(keys)
model_ids = keys[:SAMPLES_PER_PAGE]
if blind:
for key in model_ids:
rng.shuffle(models_by_id[key])
ok = True
if request.method == 'POST':
all_samples_results = []
for id in model_ids:
models = models_by_id[id]
result = {
'id': id,
'is_prompted': models[0]['is_prompted'],
'models': {}
}
all_samples_results.append(result)
for model in models:
rating = request.form[model['model_id']]
if rating:
rating = int(rating)
assert rating <= MAX_RATING and rating >= 1
result['models'][model['xp'].sig] = rating
model['rating'] = rating
else:
ok = False
model['errors'].append('Please rate this model.')
if ok:
result = {
'results': all_samples_results,
'seed': seed,
'user': user,
'blind': blind,
'exclude_prompted': exclude_prompted,
'exclude_unprompted': exclude_unprompted,
}
print(result)
with open(result_file, 'w') as f:
json.dump(result, f)
seed = seed + 1
return redirect(url_for(
'survey', signature=signature, blind=blind, seed=seed,
exclude_prompted=exclude_prompted, exclude_unprompted=exclude_unprompted,
max_epoch=max_epoch, success=True))
ratings = list(range(1, MAX_RATING + 1))
return render_template(
'survey.html', ratings=ratings, blind=blind, seed=seed, signature=signature, success=success,
exclude_prompted=exclude_prompted, exclude_unprompted=exclude_unprompted, max_epoch=max_epoch,
experiments=experiments, models_by_id=models_by_id, model_ids=model_ids, errors=[],
ref_name=ref_name, already_filled=result_file.exists())
@app.route('/audio/<path:path>')
def audio(path: str):
full_path = Path('/') / path
assert full_path.suffix in [".mp3", ".wav"]
return full_path.read_bytes(), {'Content-Type': 'audio/mpeg'}
def mean(x):
return sum(x) / len(x)
def std(x):
m = mean(x)
return math.sqrt(sum((i - m)**2 for i in x) / len(x))
@app.route('/results/<signature>')
@ensure_logged
def results(signature):
survey_path = surveys / signature
assert survey_path.exists(), survey_path
result_folder = survey_path / 'results'
result_folder.mkdir(exist_ok=True)
# ratings per model, then per user.
ratings_per_model = defaultdict(list)
users = []
for result_file in result_folder.iterdir():
if result_file.suffix != '.json':
continue
with open(result_file) as f:
results = json.load(f)
users.append(results['user'])
for result in results['results']:
for sig, rating in result['models'].items():
ratings_per_model[sig].append(rating)
fmt = '{:.2f}'
models = []
for model in sorted(ratings_per_model.keys()):
ratings = ratings_per_model[model]
models.append({
'sig': model,
'samples': len(ratings),
'mean_rating': fmt.format(mean(ratings)),
# the value 1.96 was probably chosen to achieve some
# confidence interval assuming gaussianity.
'std_rating': fmt.format(1.96 * std(ratings) / len(ratings)**0.5),
})
return render_template('results.html', signature=signature, models=models, users=users)
|