Comments (1)
With #![feature(generic_const_exprs)]
, could do something like:
fn flatten_tail<Inp, Inner, Out, const M: usize>(inp: Inp) -> Out
where
Inp: Tensor<Array = [Inner; M]>,
Inner: CountElements,
Out: Tensor<Array = [[Inner::Dtype; Inner::NUM_ELEMENTS]; M]>,
{
todo!();
}
fn main() {
let t: Tensor3D<2, 28, 28> = Default::default();
let f: Tensor2D<2, 784> = flatten_tail(t);
}
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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
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- 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 1
- can not perform tensor operations (add/sub/mul/...) on tensors with non float datatype
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