tinygrad

History

George Hotz 232ed2af3f more test cleanups (#2631 ) * more test cleanups * move test example back		2023-12-05 16:17:57 -08:00
..
README	start on mlperf models	2023-05-10 16:30:49 -07:00
helpers.py	Add MLPerf UNet3D model (#775 )	2023-05-28 20:38:19 -07:00
metrics.py	Add MLPerf UNet3D model (#775 )	2023-05-28 20:38:19 -07:00
model_eval.py	more test cleanups (#2631 )	2023-12-05 16:17:57 -08:00
model_spec.py	move things, clean up extra (#2292 )	2023-11-13 20:18:40 -08:00
model_train.py	with Tensor.train() (#1935 )	2023-09-28 18:02:31 -07:00

README

Each model should be a clean single file.
They are imported from the top level `models` directory

It should be capable of loading weights from the reference imp.

We will focus on these 5 models:

# Resnet50-v1.5 (classic) -- 8.2 GOPS/input
# Retinanet
# 3D UNET (upconvs)
# RNNT
# BERT-large (transformer)

They are used in both the training and inference benchmark:
https://mlcommons.org/en/training-normal-21/
https://mlcommons.org/en/inference-edge-30/
And we will submit to both.

NOTE: we are Edge since we don't have ECC RAM