# Typesafe Tensors

The distinctive feature of Nexus is **typesafe** tensors.

In Nexus, a tensor is typed using a tuple of axis labels.

```
val image: FloatTensor[(Width, Height, Channel)]
```

This is in contrast with common deep learning libraries, where multidimensional arrays (tensors) all belong to one type (given the element type). For example, a tensor with float is typed as `numpy.ndarray`

in NumPy and `torch.FloatTensor`

in PyTorch, no matter how many dimensions are there (rank) in the tensor, or what each axis means in the tensor.