* Fix examples
* Remove training in parameters
* Simplify a bit
* Remove extra import
* Fix linter errors
* factor out Device
* NumPy-like semantics for Tensor.__getitem__ (#506)
* Rewrote Tensor.__getitem__ to fix negative indices and add support for np.newaxis/None
* Fixed pad2d
* mypy doesn't know about mlops methods
* normal python behavior for out-of-bounds slicing
* type: ignore
* inlined idxfix
* added comment for __getitem__
* Better comments, better tests, and fixed bug in np.newaxis
* update cpu and torch to hold buffers (#542)
* update cpu and torch to hold buffers
* save lines, and probably faster
* Mypy fun (#541)
* mypy fun
* things are just faster
* running fast
* mypy is fast
* compile.sh
* no gpu hack
* refactor ops_cpu and ops_torch to not subclass
* make weak buffer work
* tensor works
* fix test failing
* cpu/torch cleanups
* no or operator on dict in python 3.8
* that was junk
* fix warnings
* comment and touchup
* dyn add of math ops
* refactor ops_cpu and ops_torch to not share code
* nn/optim.py compiles now
* Reorder imports
* call mkdir only if directory doesn't exist
---------
Co-authored-by: George Hotz <geohot@gmail.com>
Co-authored-by: Mitchell Goff <mitchellgoffpc@gmail.com>
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* vgg7 implementation - not the best, but it works
* VGG7 implementation: Spread nansbane to deter NaNs, maybe improved training experience
* VGG7 implementation: Fix training, for real this time
Results actually attempt to approximate the input
* VGG7 implementation: Sample probability management