tinygrad

mirror of https://github.com/tinygrad/tinygrad.git synced 2026-06-24 02:14:17 +00:00

History

chenyu 826cccd54d fix mean underflow for half tensor (#4377 ) * fix mean underflow for half tensor divide only the reduce factor. added unit test and non-nan assertion in resnet training. also added a failed test cast for symbolic shape var * skip for python backend		2024-05-01 13:38:57 -04:00
..
training_submission_v4.0/tinycorp	mlperf/resnet: update tinybox_red parameters to new best values (#4364 )	2024-04-30 18:08:12 -04:00
dataloader.py	pad first batch of imagenet dataloader and update eval (#4368 )	2024-05-01 00:21:52 -04:00
helpers.py	BERT: Checkpoint loading tests (#4359 )	2024-04-30 14:43:41 -04:00
initializers.py	MLPerf BERT: Main training loop (#4288 )	2024-04-29 14:35:27 -04:00
losses.py	[MLPerf][UNet3D] Add DICE loss + metrics (#4204 )	2024-04-17 20:09:33 -04:00
lr_schedulers.py	fp16 resnet (without expand backwards sum in float, doesn't work) (#3816 )	2024-03-28 01:25:37 -04:00
metrics.py	[MLPerf][UNet3D] Add DICE loss + metrics (#4204 )	2024-04-17 20:09:33 -04:00
model_eval.py	pad first batch of imagenet dataloader and update eval (#4368 )	2024-05-01 00:21:52 -04:00
model_spec.py	move globalcounters to ops (#2960 )	2024-01-01 14:21:02 -08:00
model_train.py	fix mean underflow for half tensor (#4377 )	2024-05-01 13:38:57 -04:00
README	start on mlperf models	2023-05-10 16:30:49 -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