tinygrad/.gitignore

__pycache__
notebooks
.*.swp
.*.swo
*.pyc
build
dist
*.egg-info
/env
a.out
boxes.jpg
weights/*
start tinygrad 2020-10-18 13:57:01 +08:00			`__pycache__`
			`notebooks`
			`.*.swp`
add pad2d on GPU 2020-11-08 02:46:36 +08:00			`.*.swo`
[WIP] YOLO working on tinygrad! (#245) * Some progress on yolov3 * Removed some debugging comments… Also, the forward pass eats all RAM for some reason * forward pass almost runs * forward pass runs almost * forward pass runs, now we gotta load the weights * loading weights works * fetches config and weights * everything kind of works, postprocessing of output still needs to be implemented, temp_process_results kind of works, but its kind of terrible, and not how things should be done * some changes * fixed some bugs in the forward pass and load_weights function, now outputs more correct values, however some values are still loaded incorrectly * Something is wrong with the forward pass, Conv2d tests added * forward pass almost outputs correct values, gotta fix one more thign * yolo works * some final changes * reverting changes * removed dataloader * fixed some indentation * comment out failing test, somehow it fails CI even though it passes on my computer… * fixed wrong probabilities * added webcam option to YOLO, now just need to add bounding boxes and speed it up * some progress towards adding bounding boxes * trying to speed up yolo layer on GPU, still faster on CPU but with 30GB ram usage * Faster inference times, bounding boxes added correctly, webcam works, but is slow, and there is a memory leak when running on CPU... Also added tinygrads output on the classic dog image * removed some debugging print statements * updated result image * something weird is going on, mean op on GPU tensor randomly faults, copying a tensor from GPU->CPU takes 10+ seconds… 2021-04-26 09:06:52 +08:00			`*.pyc`
add setup.py and change imports to relative 2020-10-26 23:19:50 +08:00			`build`
			`dist`
			`*.egg-info`
add pad2d on GPU 2020-11-08 02:46:36 +08:00			`/env`
Support for Apple Neural Engine (#130) * ane query is success * cite and build instructions * low level access, need to disable AMFI * coreml_ane works * coreml fun * more work * compiled example * progress * compiler works * model flow * TODOs in the readme * put some real weights in * we are learning objc * much progress i think * signed model still doesn't work * working example * there are float16 * clean up: part 1 * h11ane header, more cleanup * cleanup DeviceController creation * remove the stupid sleep * notes * start a hwx parser * no tabs * compare stuff * hmm, why don't inputs work * cache doesn't seem to fix it * hmm, the issue was the compiler * fix the compiler, guess i didn't put in weights * logging for compiler * uselessness in plist * remove hwx before compile, weights are converted to float16 * better compare * better compare * last line in comparE * opcodes from compiler * notes 2020-12-04 02:32:26 +08:00			`a.out`
use tinynn for Conv2d 2021-10-31 10:40:44 +08:00			`boxes.jpg`
works at work 2022-09-06 23:06:11 +08:00			`weights/*`