* streamlined numerical_jacobian
* Got rid of the g loop in Conv2D.forward
* ereased stupid line
* nothing
* no loops in Conv2D forward
* Conv2D backprop improved
* stupid things in examples
* alternative to einsum
* Conv2D backward einsum alternative
* tidying up
* tidied up
* no ravel
* got rid of print
* Update efficientnet.py
* Update efficientnet.py
* Update efficientnet.py
* only tensordot
* 255.0
* whitespace
* aspect ratio error in efficientnet
* noprint
Co-authored-by: Marcel Bischoff <marcel@Marcels-iMac.local>
* copy tensors to and from gpu
* add on GPU
* adding works
* we stick shapes in
* works on cpu and gpu
* test changes, not passing yet
* something else
* op tests pass
* add, mean, and sum have working forward/backward
* mul ops test
* no gpu support, no problem
* test pass, clean up later
* gpu cleanup
* cleanup test ops, don't let div fail
* revert more
* aimpler dispatcher
* clean up grad
* GPU and
* grad is a Tensor now
* gate test on GPU
* cleanups
* late loading gpu
* GPU as input option
* last cleanups
* streamlined numerical_jacobian
* Got rid of the g loop in Conv2D.forward
* ereased stupid line
* nothing
* no loops in Conv2D forward
* Conv2D backprop improved
Co-authored-by: Marcel Bischoff <marcel@Marcels-iMac.local>
* install the pytorch cpu only version
* get rid of torch gpu version
* test passed seems to get rid of invalid gpu error
* added the libs to requirements.txt
* lol
* Actions sloccount check for < 1000 lines (tests and source)
* Sudo lol
* Test sloccount in actions ci
* More tests for the expression
* apt install test to do validation in cli
* fuck test
* try something that probably won't work
* ofcourse not
* test that test fails if lines greater than 1000
* more than 1000 results in 1,000 not 1000. Delete
* remove test lines. Should pass now
* Untouch file
Untouched a file that was changed in testing
