Comments (5)
Sorry but this is for reporting issues in torchnet, not for general Torch questions.
https://github.com/torch/nn/blob/master/doc/criterion.md#msecriterion
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I think the problem is still exist.
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Yes, you cannot just use any criterion. The MNIST example is for classification, whereas MSE should be used for regression. This can be found in the Torch nn documentation.
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Thank you.
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I suspect returning vector in getIterator(mode) {...} is not work.
(specifically, variable 'load' in ListDataset cannot contain vector as target.
target = torch.LongTensor(1,10) or target = torch.LongTensor(10, 1)
(instead of original line,
target = torch.LongTensor{dataset.label[idx] + 1} )
make error.
Will you have a plan to enhance it near some day?
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Related Issues (20)
- Document uncorrect about "transform.perm"
- for ListDataset, add an onComplete argument HOT 2
- OptimEngine.test not implemented HOT 2
- fatal thread panic on parallelDatasetIterator HOT 1
- Improve ParallelDatasetIterator documentation HOT 13
- IndexedDataset using string as index for large dataset HOT 4
- returning vector in ListDataset problem. HOT 2
- This error is unclear - what is the problem with my code that is causing this? HOT 3
- Segmentation fault (core dumped) HOT 8
- Bug report: not entering into iterator until thorough depth. HOT 2
- ClassErrorMeter throwing size mismatch error HOT 1
- meter.MultilabelConfusionMeter invalid argument error HOT 1
- some bugs of transform.merge() HOT 1
- bug in transform.tablemergekeys() HOT 1
- Unable to install qlua, and therefore: qlua: module 'torchnet' not found HOT 1
- Hi, I doubt that whether I can use torchnet in win10 64x. Could anybody tell me? HOT 2
- "not enough memory" with small dataset when nthread>1 for ParallelDatasetIterator HOT 4
- How to add torchnet to a custom package on kaggle HOT 1
- RecursionError with meter.ConfusionMeter
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