Hello,

I am working on factor analysis model using greta on large count and binary matrices where most values are zero. I know it is possible to convert R Matrix `dgCMatrix`

format to numpy sparse arrays with reticulate. So, I am wondering if it is straightforward to add support for sparse matrices in `greta::as_data`

.

Also on the topic of large data, in the current version is it possible to change the dtype of tensor objects from `float64`

to `float32`

or from `int64`

to `int32`

/`int16`

to reduce memory footprint of the data and large parameter tensors?

Thanks a lot,

Vitalii