2025-09-24 02:40:50,004 [INFO ] [logger.py:dumpArgs:73]	 Starting with arguments
{"name": "cifar10", "dataset": {"path": "../../datasets/cifar10", "image_size": 224}, "batch_size": 50, "split": "train", "output": "./models/mean/", "verbose": 1, "cuda_index": 1}
2025-09-24 02:40:50,004 [INFO ] [learn_mean_imputator.py:<module>:35]	 Starting to learn mean for cifar10
2025-09-24 02:40:50,004 [INFO ] [loader.py:getDatasetSplits:21]	 Loading CIFAR10 dataset from ../../datasets/cifar10
2025-09-24 02:40:50,004 [INFO ] [baselines.py:createCIFAR10Dataset:102]	 Using 10 CIFAR10 targets: ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
2025-09-24 02:40:50,041 [INFO ] [baselines.py:getTransform:24]	 Resizing images from 32 to 224
2025-09-24 02:40:50,042 [INFO ] [baselines.py:getTransform:37]	 Applying CIFAR10 standard normalization
2025-09-24 02:40:54,506 [INFO ] [torch_utils.py:split:72]	 Split training from 50000 into 35000 training images and 15000 validation images. Found 10000 testing images.
2025-09-24 02:40:54,534 [INFO ] [util.py:selectDevice:88]	 Using cuda:1 for tensor calculations
2025-09-24 02:40:54,641 [INFO ] [learn_mean_imputator.py:<module>:53]	 Using dataset split train
2025-09-24 02:40:54,641 [INFO ] [learn_mean_imputator.py:<module>:59]	 Started learning cifar10 mean
2025-09-24 02:40:54,717 [INFO ] [imputator.py:meanFromDataloader:126]	 Output shape: torch.Size([3, 224, 224])
2025-09-24 02:41:28,837 [INFO ] [imputator.py:meanFromDataloader:134]	 Computed dataset mean in 34.196024608798325 seconds
2025-09-24 02:41:28,838 [INFO ] [learn_mean_imputator.py:<module>:65]	 Saving mean to ./models/mean/cifar10.pklz
