Comments (4)
erodner
commented on May 26, 2024
The term "incorrect metrics" would imply a bug in the implementation of the performance measure. It would be great if you can point us to the piece of source code where you suspect an error. It is also hard for us to reproduce "your results" without having the dataset and especially the way you split it into training and testing subsets.
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zygmuntz
commented on May 26, 2024
@erodner Yeah, I know. I'd suggest you try any dataset, any split, with testing images significantly smaller than training images (for example 2x2 or 3x3 smaller). My hunch is you'll be able to reproduce the phenomenon.
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cabrust
commented on May 26, 2024
Please share at least your network configuration. It may contain parts that are incompatible with hybrid training.
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zygmuntz
commented on May 26, 2024
@clrokr Sent by email. Let me know if you need anything else.
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Related Issues (20)
- Error moving to GPU HOT 2
- Multidimensional Labels HOT 2
- Minimal working example for training net. HOT 2
- ERR [ ErrorLayer::CreateOutputs(48) ] Inputs need the same number of elements! HOT 3
- High CPU, no GPU utilization in training HOT 2
- Bus error when testing HOT 6
- Commenting out #method=patch doesn't work in arch file
- ERR [ Tensor::Deserialize(303) ] Memory map failed: 12 / bad alloc HOT 4
- questions: batch size in hybrid mode; training and testing tensors
- Multiple GPUs HOT 1
- License in OpenCL kernels are GPL3, while main project is BSD 3-clause HOT 1
- Problem about HOT 3
- Problem with bad_alloc error HOT 2
- Network from the cn24 paper HOT 1
- Licensing issue with libreadline HOT 1
- FATAL: Layer has dynamic input but doesn't support it: Confusion Matrix Layer HOT 1
- Training with more than four channels HOT 2
- Compilation issue on windows 10
- how to set GPU HOT 1
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