Closed dselivanov closed 5 years ago
I agree. I will work on this. I think this will add one copy ( https://pytorch.org/docs/stable/tensors.html#torch.Tensor.to ) but faster computation should compensate.
Also agree with numpy naming.
Now float32 is the default numeric type. I will make sure that when we add a dtype = "float64" to tensor
, R won't copy the tensor again.
This is done. I added some docs here on how our wrapper converts R objects to Tensors. https://dfalbel.github.io/torch/articles/tensors.html
I believe it makes sense to make
kFloat
as default type for numeric values. Reasons are following:<float32>
tensors consumes 2x less memory and GPU memory is expensive resourceAlso may be we should follow
numpy
naming conventions fordtype
-float32
,float64
, etc