Comments (3)
torch 1.7.0 It works.
- in dataset/cifar100.py
replace all the "self.train_data" and "self.test_data" with "self. data" ; "self.train_labels" and "self.test_labels" -> "self.targets" - helper/util.py line:55
replace "view(-1)" with "reshape(-1)"
More details in the definition of torchvision/datasets/cifar.py: class CIFAR10
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just like: img, target = self.data[index], self.targets[index] for 1.7.0
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This issue is caused by the version of pyTorch. As version updated, the source code of torchvision.datasets.CIFAR100 also has been updated. This issue can be resolved simply replace datasets.CIFAR100 by source code from [here].(https://pytorch.org/docs/0.4.0/_modules/torchvision/datasets/cifar.html#CIFAR10)
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Related Issues (20)
- Cross modal KD implementation release? HOT 1
- Question on memory consumption for CRD loss when the dataset is very large HOT 3
- Why "opt.nce_k" in dataset cifar100 is 16384? How can I get this ? HOT 2
- test HOT 2
- Error while running the code
- Training scheme for linear probe on STL10 and TinyImagenet
- Problem of the order of the normalization in Similarity-Preserving loss.
- resnet structure seems to be a bit wrong HOT 3
- Failed to download the teacher models HOT 2
- about using the resnet models for cifar10 HOT 1
- crd used in image enhancement task like Denoise\SR\Deblur.
- Ensemble Task Implementation HOT 2
- Question about normalization constant Z_v1 and Z_v2 in the ContrastMemory
- Why using log_softmax instead of softmax? HOT 1
- Hyperparameter Settings for KD on Imagenet
- Is Ensemble distillation also included?
- the result is different in resnet56 HOT 1
- ERROR :run ./fetch_pretrained_teachers.sh HOT 1
- How to use myself datasets? HOT 1
- No dev set split
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