Hi,

In Flux models (created using Chain), we give data array of the format `D x N`

(`D`

- data dimension, `N`

- number of samples). This is is different from other ML libraries such as Tensorflow/PyTorch where we use `N x D`

format.

This also results in the output (for a scalar prediction) being a `1 x N`

matrix rather than a `N`

dimensional vector (which is more intuitive, atleast to me).

I am curious to know what is the reason for this design?

Thanks,

Vishnu