there's two bugs here.

1. the check for a layer id is incorrect and should be >= 0 since layer
   0 is valid
2. if both tensors have an layer identifier, it will only compare the
   layer id which will return 0 if the tensors are in the same layer.
   instead it should fallback to comparing the full tensor name

* convert: return bytes written

* ggml flavor mxfp4

* simplify jit conversion

* comment

The recent memory management changes caused all GPUs to be visible
to the runner, regardless of whether they are ultimately used. This
caused CUDA devices to allocate a primary context (~300 MB VRAM) on
each GPU, for each model. This is unnecessary, so we can both avoid
touching GPUs that we exclude in the early stage of allocation and
freeing the memory for any that we touch but don't use.

The issue will continue to exist for the old engine, since it touches
all devices during initialization.