Suppress spurious lr_scheduler.step() warning from PyTorch

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

src/training/train_gtauav.py

@@ -11,6 +11,7 @@ import json
 import logging
 import math
 import time
+import warnings
 from dataclasses import dataclass, field
 from pathlib import Path
 
@@ -317,10 +318,13 @@ def train(cfg: TrainConfigGTAUAV) -> None:
     steps_per_epoch = len(train_loader)
     total_steps = cfg.epochs * steps_per_epoch
     warmup_steps = cfg.warmup_epochs * steps_per_epoch
-    scheduler = LambdaLR(
+    with warnings.catch_warnings():
-        optimizer,
+        warnings.filterwarnings("ignore", message=".*lr_scheduler.step.*optimizer.step.*")
-        lr_lambda=_cosine_warmup_schedule(warmup_steps, total_steps),
+        scheduler = LambdaLR(
-    )
+            optimizer,
+            lr_lambda=_cosine_warmup_schedule(warmup_steps, total_steps),
+            last_epoch=-1,
+        )
     scaler = GradScaler(enabled=cfg.use_amp)
 
     # Restore optimizer/scheduler/loss state on resume.
@@ -385,7 +389,9 @@ def train(cfg: TrainConfigGTAUAV) -> None:
                 )
             scaler.step(optimizer)
             scaler.update()
-            scheduler.step()
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore", message=".*lr_scheduler.step.*optimizer.step.*")
+                scheduler.step()
 
             for key, val in loss_dict.items():
                 agg[key] = agg.get(key, 0.0) + float(val.item())