# `ExTorch.Layout`

A ``torch.layout`` is an object that represents the memory layout of a ``torch.Tensor``.
Currently, we support ``torch.strided`` (dense Tensors) and have beta support for
``torch.sparse_coo`` (sparse COO Tensors).

``torch.strided`` represents dense Tensors and is the memory layout that is
most commonly used. Each strided tensor has an associated ``torch.Storage``,
which holds its data. These tensors provide multi-dimensional, strided view of a storage.
Strides are a list of integers: the k-th stride represents the jump in the memory
necessary to go from one element to the next one in the k-th dimension of the Tensor.
This concept makes it possible to perform many tensor operations efficiently.

# `layout`

```elixir
@type layout() :: :strided | :sparse | nil
```

A ``torch.layout`` is an object that represents the memory layout of a ``torch.Tensor``.
`nil` is only used when copying layouts between tensors.

# `is_layout`
*macro* 

---

*Consult [api-reference.md](api-reference.md) for complete listing*