Comments (3)
pclucas14
commented on June 16, 2024
Note that torch.einsum, torch.matmul and torch.mm also fall into this category
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Daulbaev
commented on June 16, 2024
odeint function from https://github.com/rtqichen/torchdiffeq/ also falls.
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zou3519
commented on June 16, 2024
Actionable: check if this is still valid, file new issues for the comments in this thread
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Related Issues (20)
- Add pytorch 1.13.1 compatibility HOT 3
- Unit Test Error When Testing vmap With Missing Module "autograd_function_db" HOT 7
- Will pmap be supported in functorh？ HOT 2
- How to get only the last few layers' gradident? HOT 2
- [Question] Packaging policy for `functorch` and `torch.func` HOT 5
- INTERNAL_ASSERT failed HOT 4
- RuntimeError: Batching rule not implemented for aten::is_same_size. We could not generate a fallback.
- Vmap and backward hook problem HOT 1
- item() support for vmap HOT 2
- Performance drop because of not yet implemented batching rule for bincount
- Use functional models inside usual nn.Module HOT 1
- Error about using a grad transform with in-place operation is inconsistent with and without DDP HOT 1
- How to get the jacobian matrix in GCNs?
- Per-sample-gradient: Get gradient 0 when using grad(params_tograd, params) with respect to part of model's parameters HOT 1
- Can I call torch.utils.data.WeightedRandomSampler inside vmap? HOT 1
- vmap fails if your model includes full_backward_hook in pytorch2.0 HOT 1
- wrapper->level().value() <= current_level INTERNAL ASSERT FAILED at "../aten/src/ATen/functorch/ADInterpreters.cpp":39 HOT 1
- Swapping 2 columns in a 2d tensor
- vmap does not support Tensor.clone()
- Small difference between functorch grads and torch.autograd.grad
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