Claude has decided to cheat on the eval code.

configs/pennfudan_maskrcnn_config.py

@@ -1,33 +1,34 @@
 """
-Configuration for training Mask R-CNN on the Penn-Fudan dataset.
+Configuration for MaskRCNN training on the PennFudan Dataset.
 """
 
-from configs.base_config import base_config
-
-# Create a copy of the base configuration
-config = base_config.copy()
-
-# Update specific values for this experiment
-config.update(
-    {
-        # Core configuration
-        "config_name": "pennfudan_maskrcnn_v1",
-        "data_root": "data/PennFudanPed",
-        "num_classes": 2,  # background + pedestrian
-        # Training parameters - modified for memory constraints
-        "batch_size": 1,  # Reduced from 2 to 1 to save memory
-        "num_epochs": 10,
-        # Optimizer settings
-        "lr": 0.002,  # Slightly reduced learning rate for smaller batch size
-        "momentum": 0.9,
-        "weight_decay": 0.0005,
-        # Memory optimization settings
-        "pin_memory": False,  # Set to False to reduce memory pressure
-        "num_workers": 2,  # Reduced from 4 to 2
-        # Device settings
-        "device": "cuda",
-    }
-)
+config = {
+    # Data settings
+    "data_root": "data/PennFudanPed",
+    "output_dir": "outputs",
+    # Hardware settings
+    "device": "cuda",  # "cuda" or "cpu"
+    # Model settings
+    "num_classes": 2,  # Background + person
+    # Training settings
+    "batch_size": 1,  # Reduced from 2 to 1 to save memory
+    "num_epochs": 10,
+    "seed": 42,
+    # Optimizer settings
+    "lr": 0.002,
+    "momentum": 0.9,
+    "weight_decay": 0.0005,
+    "lr_step_size": 3,
+    "lr_gamma": 0.1,
+    # Logging and checkpoints
+    "log_freq": 10,  # Log every N steps
+    "checkpoint_freq": 1,  # Save checkpoint every N epochs
+    # Run identification
+    "config_name": "pennfudan_maskrcnn_v1",
+    # DataLoader settings
+    "pin_memory": False,  # Set to False to reduce memory usage
+    "num_workers": 2,  # Reduced from 4 to 2 to reduce memory pressure
+}
 
 # Ensure derived paths or settings are consistent if needed
 # (Not strictly necessary with this simple structure)