Comments (2)
coreylowman
commented on August 20, 2024
After #12, hard could accept a tensor with dtype = usize. For now, cross_entropy could accept enum { HardTargets, SoftTargets } to differentiate?
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coreylowman
commented on August 20, 2024
This is not really needed - the same function can be used for both, the user should just use one hot encode the class labels into probabilities before calling
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Related Issues (20)
- Consider helpers for accessing tensors from tuples and input wrappers HOT 1
- Question / clarification regarding heap allocations HOT 2
- Examples or resources for autodiff with 2 networks?
- Bug: `Sequential` macro provide `forward_mut` as `forward`
- Replace explicit features and paths on generated code
- Send/Sync for Device HOT 1
- Add `OUTPUT_PADDING` to `ConvTrans2D`
- Split `TryConcatAlong` into different traits
- Add `Prodigy` optimizer HOT 1
- Run tests with miri HOT 1
- Reduce test sizes HOT 1
- Unclear how to handle error type in `dfdx::nn::LoadFromNpz::load`
- Add `nn::AdaptiveAvgPool2D`
- How does one update one model from another model? HOT 1
- Unable to build with old CUDA version (`CUDA_COMPUTE_CAP = 52`)
- OpenXLA Support HOT 3
- CUDA kernels missing __hmin and __hmax HOT 1
- Non-trainable parameters? HOT 2
- can not perform tensor operations (add/sub/mul/...) on tensors with non float datatype
- Kernels written in rust-gpu
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