2025-05-22 10:49:07,748 [INFO ] [logger.py:dumpArgs:73]	 Starting with arguments
{"name": "celeba", "dataset": {"path": "../../datasets/CelebAMask/256/img", "lists_root": "datasets/celeba", "attributes_path": "../../datasets/CelebAMask/1024/CelebAMask-HQ-attribute-anno.txt", "targets": ["Eyeglasses"]}, "output": "./results/ece/celeba/Eyeglasses/", "classifier": "./models/dirichlet-celeba/Eyeglasses/celeba-20250514-004153.pklz", "cuda_index": 0, "batch_size": 100, "buckets": 10, "seed": 1337, "verbose": 1}
2025-05-22 10:49:07,779 [INFO ] [util.py:selectDevice:87]	 Using cuda:0 for tensor calculations
2025-05-22 10:49:07,932 [INFO ] [ece_dataset.py:<module>:61]	 Running on cuda:0
2025-05-22 10:49:07,932 [INFO ] [loader.py:getDatasetSplits:26]	 Loading CelebA dataset from ../../datasets/CelebAMask/256/img
2025-05-22 10:49:12,888 [INFO ] [celeba.py:createCelebADataset:139]	 Found 1 CelebA attributes for 30000 images: ['Eyeglasses']
2025-05-22 10:49:12,943 [INFO ] [celeba.py:createCelebADataset:149]	 Loading 26000 training images, 2000 validation images, and 2000 testing images
2025-05-22 10:49:12,943 [INFO ] [ece_dataset.py:<module>:69]	 Using dataset celeba with 2000 test samples and 1 classes
2025-05-22 10:49:13,296 [INFO ] [ece_dataset.py:<module>:76]	 Using dirichlet decision maker
2025-05-22 10:49:17,208 [INFO ] [calibration.py:computeECE:245]	 
        Computed ECE 0.0035133929923176765 in 3.910971953999251 seconds with 10 buckets:
        * Non-zero buckets: tensor([5, 6, 7, 8, 9])
        * Final bucket sizes: tensor([   3,    2,    3,    5, 1987], dtype=torch.int32) totaling 2000 samples
        * Final bucket confidences: tensor([0.5335, 0.6098, 0.7464, 0.8683, 0.9981])
        * Final bucket accuracy: tensor([1.0000, 1.0000, 0.6667, 0.8000, 0.9960])
        * Label counts: tensor([1898,  102], dtype=torch.int32)
        * Prediction Action Counts: tensor([1902,   98], dtype=torch.int32)
        * Average accuracy: 0.9950000047683716
    
