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Kunwar Raj Singh 5d3310ce56
 MaskRCNN Inference (#884) 
* MaskRCNN weights loading

* backbone maybe works

* backbone works, but resnet body atol 1e-3

* RPN Call, but veryy wrong output

* fixed topk

* RPN maybe works, not sure about nms

* Fix cursed modules

* add back editorconfig

* Full call, wrong output

* Full call works

* fix mask

* use NMS from retinanet

* Removing extra funcs

* refactor

* readable

* Add example to run model

* remove filter

* Fix split, batched inference is worse

* Fix image sizes

* Matching reference

* merge master

* add filter on top detections

* cuda backend fixed

* add model eval and spec

* convert images to rgb

* fix eval

* simplify examples code

* remove extra code

* meshgrid using tinygrad

* removing numpy

* roi align, floor, ceil

* remove numpy from level_mapper

* remove numpy from pooler

* Revert "Merge branch 'master' of github.com:kunwar31/tinygrad into mrcnn-inference"

This reverts commit 4b95a3cb49, reversing
changes made to 98f2b1fa2e.

* roi align gather

* fix master merge

* revert to old floor, ceil as ints present in domain

* use log2 op

* fix indexes

* weird bug with ints and gpu

* weird bug with ints and gpu

* refactors, add env var for gather

* floor with contiguous, where

* refactor topk, sort

* remove staticmethod

* refactor stride

* remove log2 mlop

* realize -> contiguous

* refactor forward

* remove num_classes, stride_in_1x1 from state

* refactor forward

* refactoring

* flake8

* removing numpy in anchor gen, use numpy for gather, nonzero, optimize topk

* keep using tinygrad for smaller gathers

* fix empty tensors

* comms

* move from tensor.py

* resnet test passing

* add coco dataset back

* fix spaces

* add test for log2

* no need to create Tensors

* no need to create Tensors

---------

Co-authored-by: Kunwar Raj Singh <kunwar31@pop-os.localdomain>
2023-06-25 15:37:51 -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 MaskRCNN Inference (#884) 2023-06-25 15:37:51 -07:00
model_spec.py MaskRCNN Inference (#884) 2023-06-25 15:37:51 -07:00
model_train.py feat: add train scaffolding (#859) 2023-05-30 07:10:40 -07:00
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