Files
tinygrad/examples/mlperf
chenyu a187dfd3df bert BEAM_UOPS_MAX 3000->4000 (#9603)
more stable for the final step time

green 410ms (master) -> 397ms (BEAM=4) -> 392ms (this)
red 561ms (master) -> 550ms (this)
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..
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2025-03-21 13:36:41 -04:00
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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