File size: 40,042 Bytes
6e17fd0 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 |
from sqlalchemy import create_engine, Column, Integer, Float, String, DateTime, Boolean, JSON, func, desc, exists, ForeignKey, or_, and_, case, text
from sqlalchemy.exc import OperationalError, SQLAlchemyError
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.dialects.mysql import JSON as MySQLJSON
from sqlalchemy.orm import Session, sessionmaker, aliased, relationship
from contextlib import contextmanager
from collections import defaultdict
import time
import json
from datetime import datetime, timedelta, timezone
import bittensor as bt
from typing import Optional
from model.data import ModelId
from vali_api.config import DBHOST, DBNAME, DBUSER, DBPASS, IS_PROD
Base = declarative_base()
# Global variables for engine and Session
_engine: Optional[object] = None
Session: Optional[sessionmaker] = None
def init_database():
"""
Initialize the database connection and create tables.
Must be called before using any database operations.
"""
global _engine, Session
if _engine is not None:
bt.logging.warning("Database already initialized")
return
# Try different MySQL drivers in order of preference
drivers_to_try = [
('mysql', 'mysqlclient (MySQLdb)'),
('mysql+pymysql', 'PyMySQL')
]
for driver, driver_name in drivers_to_try:
try:
connection_string = f'{driver}://{DBUSER}:{DBPASS}@{DBHOST}/{DBNAME}'
bt.logging.info(f"Attempting database connection with {driver_name}")
_engine = create_engine(connection_string)
Session = sessionmaker(bind=_engine)
# Test the connection
with Session() as session:
session.execute(text('SELECT 1'))
# Create all tables
Base.metadata.create_all(_engine)
bt.logging.info(f"Database initialized successfully with {driver_name}")
return
except ImportError as e:
bt.logging.warning(f"Driver {driver_name} not available: {e}")
continue
except Exception as e:
bt.logging.error(f"Failed to connect with {driver_name}: {e}")
if driver == drivers_to_try[-1][0]: # Last driver in list
raise
continue
raise RuntimeError("Failed to initialize database with any available MySQL driver")
def get_session() -> Session:
"""
Get a database session. Raises exception if database not initialized.
"""
if Session is None:
raise RuntimeError("Database not initialized. Call init_database() first.")
return Session()
def get_table_name(base_name: str) -> str:
"""Helper function to get the correct table name with suffix if not in production."""
return f"{base_name}{'_test' if not IS_PROD else ''}"
class ModelQueue(Base):
__tablename__ = get_table_name('sn21_model_queue')
hotkey = Column(String(255), primary_key=True)
uid = Column(String(255), primary_key=True, index=True)
block = Column(Integer, index=True)
competition_id = Column(String(255), index=True)
model_metadata = Column(JSON)
is_new = Column(Boolean, default=True)
is_being_scored = Column(Boolean, default=False)
is_being_scored_by = Column(String(255), default=None)
scoring_updated_at = Column(DateTime, default=None)
updated_at = Column(DateTime, default=datetime.utcnow)
# Relationship to use dynamic table name (lambda function)
scores = relationship(
"ScoreHistory",
back_populates="model",
foreign_keys="[ScoreHistory.hotkey, ScoreHistory.uid]",
primaryjoin=lambda: and_(
ModelQueue.hotkey == ScoreHistory.hotkey,
ModelQueue.uid == ScoreHistory.uid
)
)
def __repr__(self):
return f"<ModelQueue(hotkey='{self.hotkey}', uid='{self.uid}', competition_id='{self.competition_id}', is_new={self.is_new})>"
class ScoreHistory(Base):
__tablename__ = get_table_name('sn21_score_history')
id = Column(Integer, primary_key=True)
hotkey = Column(String(255), ForeignKey(f"{get_table_name('sn21_model_queue')}.hotkey", ondelete='SET NULL'), index=True, nullable=True)
uid = Column(String(255), ForeignKey(f"{get_table_name('sn21_model_queue')}.uid", ondelete='SET NULL'), index=True, nullable=True)
competition_id = Column(String(255), index=True)
model_metadata = Column(JSON)
score = Column(Float)
scored_at = Column(DateTime, default=datetime.utcnow)
block = Column(Integer)
model_hash = Column(String(255))
scorer_hotkey = Column(String(255), index=True)
is_archived = Column(Boolean, default=False)
metric_scores = Column(MySQLJSON, nullable=True)
wandb_run_id = Column(String(255), nullable=True)
wandb_run_url = Column(String(512), nullable=True)
# Relationship to ModelQueue using dynamic table name (lambda function)
model = relationship(
"ModelQueue",
back_populates="scores",
foreign_keys=[hotkey, uid],
primaryjoin=lambda: and_(
ModelQueue.hotkey == ScoreHistory.hotkey,
ModelQueue.uid == ScoreHistory.uid
)
)
def __repr__(self):
return f"<ScoreHistory(hotkey='{self.hotkey}', uid='{self.uid}', score={self.score}, scored_at={self.scored_at}, model_metadata={self.model_metadata} is_archived={self.is_archived})>"
class ModelIdEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, ModelId):
return {
'namespace': obj.namespace,
'name': obj.name,
'epoch': obj.epoch,
'commit': obj.commit,
'hash': obj.hash,
'competition_id': obj.competition_id
}
return super().default(obj)
class ModelQueueManager:
def __init__(self, max_scores_per_model=5, rescore_interval_hours=24, max_retries=3, retry_delay=1):
if Session is None:
raise RuntimeError("Database not initialized. Call init_database() first.")
self.session = get_session()
self.max_scores_per_model = max_scores_per_model
self.rescore_interval = timedelta(hours=rescore_interval_hours)
self.max_retries = max_retries
self.retry_delay = retry_delay
@contextmanager
def session_scope(self):
"""Provide a transactional scope around a series of operations."""
session = get_session()
try:
yield session
session.commit()
except Exception as e:
session.rollback()
raise
finally:
session.close()
def reset_session(self):
"""Reset the session in case of connection issues."""
try:
self.session.close()
except:
pass
try:
self.session = get_session()
except RuntimeError as e:
bt.logging.error(f"Failed to reset session: {str(e)}")
raise
def execute_with_retry(self, operation, *args, **kwargs):
"""Execute an operation with retry logic."""
for attempt in range(self.max_retries):
try:
return operation(*args, **kwargs)
except OperationalError as e:
if "Lost connection" in str(e) and attempt < self.max_retries - 1:
bt.logging.warning(f"Lost connection to MySQL. Attempt {attempt + 1}/{self.max_retries}. Retrying...")
self.reset_session()
time.sleep(self.retry_delay)
else:
raise
except SQLAlchemyError as e:
if attempt < self.max_retries - 1:
bt.logging.warning(f"Database error. Attempt {attempt + 1}/{self.max_retries}. Retrying...")
self.reset_session()
time.sleep(self.retry_delay)
else:
raise
def store_updated_model(self, uid, hotkey, model_metadata, updated):
"""
Store or update model metadata with retry logic.
Args:
uid (str): Model UID
hotkey (str): Model hotkey
model_metadata: Model metadata object
updated (bool): Whether this is an update
Returns:
bool: Success status
"""
def _store_model():
with self.session_scope() as session:
try:
# Query existing model with lock
existing_model = session.query(ModelQueue).filter_by(
hotkey=hotkey,
uid=uid
).with_for_update().first()
# Serialize metadata
serialized_metadata = json.dumps(model_metadata.__dict__, cls=ModelIdEncoder)
if existing_model:
if existing_model.model_metadata != serialized_metadata or existing_model.block != model_metadata.block:
bt.logging.debug(f"Updating existing model metadata for UID={uid}, Hotkey={hotkey}. Old metadata: {existing_model.model_metadata}, New metadata: {serialized_metadata}")
existing_model.model_metadata = serialized_metadata
existing_model.is_new = True
existing_model.block = model_metadata.block
existing_model.updated_at = datetime.utcnow()
else:
# Create new model entry
new_model = ModelQueue(
hotkey=hotkey,
uid=uid,
competition_id=model_metadata.id.competition_id,
model_metadata=serialized_metadata,
is_new=True,
block=model_metadata.block
)
session.add(new_model)
bt.logging.debug(f"Stored new model for UID={uid}, Hotkey={hotkey} in database. Is new = {updated}")
return True
except Exception as e:
bt.logging.error(f"Error in _store_model: {str(e)}")
bt.logging.error(f"Model metadata: {model_metadata}")
raise
try:
return self.execute_with_retry(_store_model)
except Exception as e:
bt.logging.error(f"Failed to store model after {self.max_retries} attempts: {str(e)}")
return False
def get_next_model_to_score(self, competition_id: str):
"""
Get next model to score with retry logic.
The updated prioritization logic ensures:
1. New models (highest priority)
2. Models never scored with non-zero scores
3a. High-scoring models not scored for over a week
3b. Models not scored for more than 7 days (safety net for winning models)
4. Models eligible by standard criteria (not scored in 5 days or < 5 scores)
5. Everything else (lowest priority)
Zero-scored models that are frequently scored are downgraded in priority
to prevent them from consuming too many resources.
"""
def _get_next_model():
with self.session_scope() as session:
try:
now = datetime.utcnow()
# ---- START: Query to find overall highest score ----
overall_max_score_value = session.query(func.max(ScoreHistory.score)).filter(
ScoreHistory.competition_id == competition_id,
ScoreHistory.is_archived == False,
ScoreHistory.score > 0 # Consider only positive scores as relevant for "highest"
).scalar()
if overall_max_score_value is not None:
bt.logging.info(f"Overall highest positive score in competition '{competition_id}' is: {overall_max_score_value:.4f}")
else:
bt.logging.info(f"No positive scores found for competition '{competition_id}' to determine an overall highest score.")
# ---- END: Query ----
# Get latest score timestamp and count for each model
score_subquery = session.query(
ScoreHistory.hotkey,
ScoreHistory.uid,
func.count(ScoreHistory.id).label('score_count'),
func.max(ScoreHistory.scored_at).label('latest_scored_at'), # Get the latest score timestamp
func.max(ScoreHistory.score).label('max_score') # Get the maximum score
).filter(
ScoreHistory.is_archived == False,
ScoreHistory.competition_id == competition_id,
ScoreHistory.score > 0 # Only consider non-zero scores
).group_by(
ScoreHistory.hotkey,
ScoreHistory.uid
).subquery()
# Also track all scores (including zeros) for high-frequency zero score detection
all_scores_subquery = session.query(
ScoreHistory.hotkey,
ScoreHistory.uid,
func.count(ScoreHistory.id).label('all_score_count'),
func.max(ScoreHistory.scored_at).label('latest_all_scored_at'),
func.sum(case((ScoreHistory.score > 0, 1), else_=0)).label('non_zero_count')
).filter(
ScoreHistory.is_archived == False,
ScoreHistory.competition_id == competition_id
).group_by(
ScoreHistory.hotkey,
ScoreHistory.uid
).subquery()
five_days_ago = now - timedelta(days=5)
weekly_rescore_threshold_time = now - timedelta(days=7) # Define a 7-day threshold
# Check if we have new models before proceeding
have_new_models = session.query(ModelQueue).filter(
ModelQueue.is_being_scored == False,
ModelQueue.competition_id == competition_id,
ModelQueue.is_new == True
).first() is not None
# Check if we have never-scored models
never_scored_count = session.query(func.count(ModelQueue.uid)).filter(
ModelQueue.is_being_scored == False,
ModelQueue.competition_id == competition_id,
~exists().where(
and_(
ScoreHistory.hotkey == ModelQueue.hotkey,
ScoreHistory.uid == ModelQueue.uid,
ScoreHistory.score > 0
)
)
).scalar()
# If no new models and no never-scored models, prioritize high scoring models not scored recently
if not have_new_models:
# ---- START: Modified logic for dynamic high-score threshold ----
if overall_max_score_value is not None and overall_max_score_value > 0: # Ensure we have a valid max score
dynamic_high_score_threshold = overall_max_score_value * 0.97
bt.logging.info(f"Using dynamic high-score threshold for competition '{competition_id}': >= {dynamic_high_score_threshold:.4f} (based on overall max of {overall_max_score_value:.4f})")
# First try to get a high-scoring model not scored in over a week
top_model = session.query(ModelQueue).join(
score_subquery,
and_(
ModelQueue.hotkey == score_subquery.c.hotkey,
ModelQueue.uid == score_subquery.c.uid
)
).filter(
ModelQueue.is_being_scored == False,
ModelQueue.competition_id == competition_id,
score_subquery.c.latest_scored_at < weekly_rescore_threshold_time,
score_subquery.c.max_score >= dynamic_high_score_threshold # Use dynamic threshold
).order_by(
score_subquery.c.max_score.desc() # Highest score first
).with_for_update().first()
if top_model:
# Create a dictionary with the model's attributes
model_data = {
'hotkey': top_model.hotkey,
'uid': top_model.uid,
'block': top_model.block,
'competition_id': top_model.competition_id,
'model_metadata': top_model.model_metadata,
'is_new': top_model.is_new,
'is_being_scored': top_model.is_being_scored,
'is_being_scored_by': top_model.is_being_scored_by,
'scoring_updated_at': top_model.scoring_updated_at,
'updated_at': top_model.updated_at
}
bt.logging.debug(f"Found high-scoring model (dynamic threshold) to score: hotkey={model_data['hotkey']}, uid={model_data['uid']}")
return model_data
else:
bt.logging.info(f"Skipping dynamic high-score prioritization for competition '{competition_id}' as no overall positive max score is available or it's zero.")
# ---- END: Modified logic ----
# Otherwise, use the standard prioritization logic with the zero-score detection
next_model = session.query(ModelQueue).outerjoin(
score_subquery,
and_(
ModelQueue.hotkey == score_subquery.c.hotkey,
ModelQueue.uid == score_subquery.c.uid
)
).outerjoin(
all_scores_subquery,
and_(
ModelQueue.hotkey == all_scores_subquery.c.hotkey,
ModelQueue.uid == all_scores_subquery.c.uid
)
).filter(
ModelQueue.is_being_scored == False,
ModelQueue.competition_id == competition_id
).order_by(
desc(ModelQueue.is_new), # 1. Prioritize new models
(score_subquery.c.score_count == None).desc(), # 2. Prioritize models never scored (non-zero)
case( # 3. Prioritize models not scored for more than 7 days (safety net)
(and_(score_subquery.c.latest_scored_at != None, score_subquery.c.latest_scored_at < weekly_rescore_threshold_time), 0),
else_=1
),
# 4. Decrease priority for models with all zero scores and frequent scoring
case(
(and_(
all_scores_subquery.c.all_score_count > 10, # Has many scores
all_scores_subquery.c.non_zero_count == 0, # All scores are zero
all_scores_subquery.c.latest_all_scored_at > five_days_ago # Scored recently
), 1),
else_=0
),
case( # 5. Prioritize models eligible by standard criteria
(or_(
score_subquery.c.latest_scored_at == None,
score_subquery.c.latest_scored_at <= five_days_ago,
score_subquery.c.score_count < 5
), 0),
else_=1
),
func.rand() # 6. Random tie-breaker
).with_for_update().first()
if next_model:
# Create a dictionary with the model's attributes
model_data = {
'hotkey': next_model.hotkey,
'uid': next_model.uid,
'block': next_model.block,
'competition_id': next_model.competition_id,
'model_metadata': next_model.model_metadata,
'is_new': next_model.is_new,
'is_being_scored': next_model.is_being_scored,
'is_being_scored_by': next_model.is_being_scored_by,
'scoring_updated_at': next_model.scoring_updated_at,
'updated_at': next_model.updated_at
}
bt.logging.debug(f"Found next model to score: hotkey={model_data['hotkey']}, uid={model_data['uid']}")
return model_data
else:
bt.logging.debug("No models available for scoring")
return None
except Exception as e:
bt.logging.error(f"Error in _get_next_model: {str(e)}")
raise
try:
return self.execute_with_retry(_get_next_model)
except Exception as e:
bt.logging.error(f"Failed to get next model after {self.max_retries} attempts: {str(e)}")
return None
def mark_model_as_being_scored(self, model_hotkey, model_uid, scorer_hotkey):
"""Mark model as being scored with retry logic."""
def _mark_model():
with self.session_scope() as session:
model = session.query(ModelQueue).filter_by(
hotkey=model_hotkey,
uid=model_uid
).with_for_update().first()
if model and not model.is_being_scored:
model.is_being_scored = True
model.is_being_scored_by = scorer_hotkey
model.scoring_updated_at = datetime.utcnow()
return True
return False
try:
return self.execute_with_retry(_mark_model)
except Exception as e:
bt.logging.error(f"Failed to mark model as being scored after {self.max_retries} attempts: {str(e)}")
return False
def submit_score(self, model_hotkey, model_uid, scorer_hotkey, model_hash, score, metric_scores):
"""Submit score with retry logic. Mark the model in queue as scored. Remove from queue."""
def _submit_score():
with self.session_scope() as session:
try:
model = session.query(ModelQueue).filter_by(
hotkey=model_hotkey,
uid=model_uid
).with_for_update().first()
if not model:
bt.logging.error(f"No model found for hotkey {model_hotkey} and uid {model_uid}")
return False
"""
# temporarily allow scoring from any hotkey
new_score = ScoreHistory(
hotkey=model_hotkey,
uid=model_uid,
competition_id=model.competition_id,
score=score,
block=model.block,
model_hash=model_hash,
scorer_hotkey=scorer_hotkey,
model_metadata=model.model_metadata
)
session.add(new_score)
model.is_new = False
model.is_being_scored = False
model.is_being_scored_by = None
model.scoring_updated_at = None
model.updated_at = datetime.now(timezone.utc)
bt.logging.info(f"Successfully submitted score for model {model_hotkey} by {scorer_hotkey}")
return True
"""
if model.is_being_scored and model.is_being_scored_by == scorer_hotkey:
# Extract wandb fields from metric_scores if present
wandb_run_id = None
wandb_run_url = None
if metric_scores and isinstance(metric_scores, dict):
wandb_run_id = metric_scores.get('wandb_run_id')
wandb_run_url = metric_scores.get('wandb_run_url')
new_score = ScoreHistory(
hotkey=model_hotkey,
uid=model_uid,
competition_id=model.competition_id,
score=score,
block=model.block,
model_hash=model_hash,
scorer_hotkey=scorer_hotkey,
model_metadata=model.model_metadata,
metric_scores=metric_scores,
wandb_run_id=wandb_run_id,
wandb_run_url=wandb_run_url
)
session.add(new_score)
model.is_new = False
model.is_being_scored = False
model.is_being_scored_by = None
model.scoring_updated_at = None
model.updated_at = datetime.now(timezone.utc)
bt.logging.info(f"Successfully submitted score for model {model_hotkey} by {scorer_hotkey}")
return True
else:
bt.logging.error(f"Failed to submit score for model {model_hotkey} by {scorer_hotkey}. "
f"Model: {model}, is_being_scored: {model.is_being_scored}, "
f"is_being_scored_by: {model.is_being_scored_by}")
return False
except Exception as e:
bt.logging.error(f"Error in _submit_score: {str(e)}")
raise
try:
return self.execute_with_retry(_submit_score)
except Exception as e:
bt.logging.error(f"Failed to submit score after {self.max_retries} attempts: {str(e)}")
return False
def reset_stale_scoring_tasks(self, max_scoring_time_minutes=15):
"""Reset stale scoring tasks with retry logic."""
def _reset_stale_tasks():
with self.session_scope() as session:
try:
stale_time = datetime.utcnow() - timedelta(minutes=max_scoring_time_minutes)
stale_models = session.query(ModelQueue).filter(
ModelQueue.is_being_scored == True,
ModelQueue.scoring_updated_at < stale_time
).with_for_update().all()
reset_count = 0
for model in stale_models:
model.is_being_scored = False
model.is_being_scored_by = None
model.scoring_updated_at = None
reset_count += 1
bt.logging.info(f"Reset scoring task for stale model: hotkey={model.hotkey}, uid={model.uid}")
return reset_count
except Exception as e:
bt.logging.error(f"Error in _reset_stale_tasks: {str(e)}")
raise
try:
return self.execute_with_retry(_reset_stale_tasks)
except Exception as e:
bt.logging.error(f"Failed to reset stale tasks after {self.max_retries} attempts: {str(e)}")
return 0
def get_recent_model_scores(self, scores_per_model):
"""
Get recent scores for all models.
Args:
scores_per_model (int): Number of recent scores to fetch per model
Returns:
dict: Dictionary of model scores grouped by UID
"""
def _get_recent_scores():
with self.session_scope() as session:
try:
# First, create a subquery that ranks scores by timestamp for each model
ranked_scores = (
session.query(
ScoreHistory,
func.row_number().over(
partition_by=(ScoreHistory.hotkey, ScoreHistory.uid),
order_by=desc(ScoreHistory.scored_at)
).label('score_rank')
)
.filter(ScoreHistory.is_archived == False)
.filter(ScoreHistory.score != 0)
.subquery()
)
# Get the most recent scores for each model
recent_scores = session.query(ranked_scores).filter(
ranked_scores.c.score_rank <= scores_per_model
).subquery('recent_scores')
# Join with ModelQueue to get additional model information
results = session.query(
ModelQueue.uid,
ModelQueue.hotkey,
ModelQueue.competition_id,
ModelQueue.model_metadata,
recent_scores.c.score,
recent_scores.c.scored_at,
recent_scores.c.block,
recent_scores.c.model_hash,
recent_scores.c.scorer_hotkey,
recent_scores.c.score_rank
).outerjoin(
recent_scores,
and_(
ModelQueue.hotkey == recent_scores.c.hotkey,
ModelQueue.uid == recent_scores.c.uid,
)
).order_by(
ModelQueue.uid,
ModelQueue.hotkey,
recent_scores.c.scored_at.desc()
).all()
scores_by_uid = defaultdict(lambda: defaultdict(list))
for result in results:
if result.score is not None:
# Create a unique key for each hotkey+uid combination
model_key = f"{result.hotkey}_{result.uid}"
scores_by_uid[result.uid][model_key].append({
'hotkey': result.hotkey,
'competition_id': result.competition_id,
'model_metadata': result.model_metadata,
'score': result.score,
'scored_at': result.scored_at.isoformat() if result.scored_at else None,
'block': result.block,
'model_hash': result.model_hash,
'scorer_hotkey': result.scorer_hotkey,
'rank': result.score_rank
})
else:
# Handle models with no scores
model_key = f"{result.hotkey}_{result.uid}"
if not scores_by_uid[result.uid][model_key]: # Only add if no scores exist
scores_by_uid[result.uid][model_key].append({
'hotkey': result.hotkey,
'competition_id': None,
'model_metadata': result.model_metadata,
'score': None,
'scored_at': None,
'block': None,
'model_hash': None,
'scorer_hotkey': None,
'rank': None
})
# Convert defaultdict to regular dict for return
return {
uid: dict(models)
for uid, models in scores_by_uid.items()
}
except Exception as e:
bt.logging.error(f"Error in _get_recent_scores: {str(e)}")
raise
try:
return self.execute_with_retry(_get_recent_scores)
except Exception as e:
bt.logging.error(f"Failed to get recent scores after {self.max_retries} attempts: {str(e)}")
return {}
def get_all_model_scores(self):
"""Get all model scores with retry logic."""
def _get_all_scores():
with self.session_scope() as session:
try:
# First, get the latest score timestamps
latest_scores = session.query(
ScoreHistory.hotkey,
ScoreHistory.uid,
func.max(ScoreHistory.scored_at).label('latest_score_time')
).filter(
ScoreHistory.is_archived == False
).group_by(
ScoreHistory.hotkey,
ScoreHistory.uid
).subquery('latest_scores')
# Get score details
latest_score_details = session.query(
ScoreHistory
).join(
latest_scores,
and_(
ScoreHistory.hotkey == latest_scores.c.hotkey,
ScoreHistory.uid == latest_scores.c.uid,
ScoreHistory.scored_at == latest_scores.c.latest_score_time
)
).subquery('latest_score_details')
# Get final results
results = session.query(
ModelQueue.uid,
ModelQueue.hotkey,
ModelQueue.competition_id,
latest_score_details.c.score,
latest_score_details.c.scored_at,
latest_score_details.c.block,
latest_score_details.c.model_hash,
latest_score_details.c.scorer_hotkey
).outerjoin(
latest_score_details,
and_(
ModelQueue.hotkey == latest_score_details.c.hotkey,
ModelQueue.uid == latest_score_details.c.uid
)
).all()
scores_by_uid = defaultdict(list)
for result in results:
if result.score is not None:
scores_by_uid[result.uid].append({
'hotkey': result.hotkey,
'competition_id': result.competition_id,
'score': result.score,
'scored_at': result.scored_at.isoformat() if result.scored_at else None,
'block': result.block,
'model_hash': result.model_hash,
})
else:
scores_by_uid[result.uid].append({
'hotkey': result.hotkey,
'competition_id': result.competition_id,
'score': None,
'scored_at': None,
'block': None,
'model_hash': None,
})
return dict(scores_by_uid)
except Exception as e:
bt.logging.error(f"Error in _get_all_scores: {str(e)}")
raise
try:
return self.execute_with_retry(_get_all_scores)
except Exception as e:
bt.logging.error(f"Failed to get all scores after {self.max_retries} attempts: {str(e)}")
return {}
def archive_scores_for_deregistered_models(self, registered_hotkey_uid_pairs):
"""Archive deregistered models with retry logic."""
def _archive_scores():
with self.session_scope() as session:
try:
all_models = session.query(
ModelQueue.hotkey,
ModelQueue.uid
).with_for_update().all()
deregistered_models = set(
(model.hotkey, model.uid) for model in all_models
) - set(registered_hotkey_uid_pairs)
for hotkey, uid in deregistered_models:
# Mark scores as archived
archive_result = session.query(ScoreHistory).filter_by(
hotkey=hotkey,
uid=uid,
is_archived=False
).update(
{"is_archived": True},
synchronize_session=False
)
# Remove from ModelQueue
delete_result = session.query(ModelQueue).filter_by(
hotkey=hotkey,
uid=uid
).delete(synchronize_session=False)
bt.logging.debug(
f"Processed deregistered model - Hotkey: {hotkey}, "
f"UID: {uid}, Archived scores: {archive_result}, "
f"Removed from queue: {delete_result}"
)
return len(deregistered_models)
except Exception as e:
bt.logging.error(f"Error in _archive_scores: {str(e)}")
raise
try:
result = self.execute_with_retry(_archive_scores)
print(f"Archived scores and removed {result} deregistered models from the queue.")
return result
except Exception as e:
bt.logging.error(f"Failed to archive scores after {self.max_retries} attempts: {str(e)}")
return 0
def close(self):
"""Safely close the session."""
try:
self.session.close()
except:
pass
|