Add multiple dtype support

[coreylowman]

This will be another generic parameter of all tensors. Most existing operations will likely require float generic.

Related to #9 since it involves an additional generic parameter

[coreylowman]

Next step for this is to make Device traits generic against dtype... first attempt ballooned into a huge number of changes in tensor though

[coreylowman]

Device traits are now generic against dtype. Tensor's have dtype as well, but all tensor_ops hard code Dtype=f32. Next step should be add Dtype as generic on tensor and adding Dtype: Float restrictions to most tensor ops.

[coreylowman]

Unclear how necessary this is. Previously the main use case I was thinking of was for class labels, but I don't think its worth supporting all the different data types in tensors just for that, especially since we can just one hot encode the class labels into f32 tensors anyway (see #19).

Now the main use cases I can think of are:

• using f64 instead of f32, or maybe f16.
• quantization

Both of those are pretty low priority though

[coreylowman]

Closing this for now since at least there are hooks to add other dtypes. If a new dtype should be added, there should be an issue created for that specific dtype