2025-05-22 10:47:40,120 [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": ["Blond_Hair"]}, "output": "./results/ece/celeba/Blond_Hair/", "classifier": "./models/dirichlet-celeba/Blond_Hair/celeba-20250514-005354.pklz", "cuda_index": 0, "batch_size": 100, "buckets": 10, "seed": 1337, "verbose": 1}
2025-05-22 10:47:40,145 [INFO ] [util.py:selectDevice:87]	 Using cuda:0 for tensor calculations
2025-05-22 10:47:40,254 [INFO ] [ece_dataset.py:<module>:61]	 Running on cuda:0
2025-05-22 10:47:40,254 [INFO ] [loader.py:getDatasetSplits:26]	 Loading CelebA dataset from ../../datasets/CelebAMask/256/img
2025-05-22 10:47:45,136 [INFO ] [celeba.py:createCelebADataset:139]	 Found 1 CelebA attributes for 30000 images: ['Blond_Hair']
2025-05-22 10:47:45,191 [INFO ] [celeba.py:createCelebADataset:149]	 Loading 26000 training images, 2000 validation images, and 2000 testing images
2025-05-22 10:47:45,191 [INFO ] [ece_dataset.py:<module>:69]	 Using dataset celeba with 2000 test samples and 1 classes
2025-05-22 10:47:45,438 [INFO ] [ece_dataset.py:<module>:76]	 Using dirichlet decision maker
2025-05-22 10:47:49,246 [INFO ] [calibration.py:computeECE:245]	 
        Computed ECE 0.004570013843476772 in 3.806016820948571 seconds with 10 buckets:
        * Non-zero buckets: tensor([5, 6, 7, 8, 9])
        * Final bucket sizes: tensor([  51,   76,   98,  127, 1648], dtype=torch.int32) totaling 2000 samples
        * Final bucket confidences: tensor([0.5538, 0.6491, 0.7534, 0.8552, 0.9879])
        * Final bucket accuracy: tensor([0.4902, 0.6711, 0.7449, 0.8661, 0.9891])
        * Label counts: tensor([1668,  332], dtype=torch.int32)
        * Prediction Action Counts: tensor([1709,  291], dtype=torch.int32)
        * Average accuracy: 0.9445000290870667
    
