What is "splatting" in flux (loss?)?

Specific Domains Machine Learning
1

In the Flux docs for train! it says

In case datapoints d are of numeric array type, assume no splatting is needed and compute the gradient of loss(d) .

What does “splatting” mean here?

I am guessing that what this means is that, if the data are expressed as matrices (dimensions X datapoints) or maybe the other way around, the loss function can be written to operate on multiple datapoints at once. Is this correct?

If so, then does Flux assume that if the data are in a matrix, that the loss must operate on the whole matrix at once?

2

It may not be specific to Flux, just the splat operator ....

3

ok my guess was completely wrong…

did not know the “…” is called splat, was thinking it had something to with gather/scatter