* enumerate cases of Tensors in the JIT
* optional fused optimizers
* add fused optimizer test
* move that there
* ugh
* work on beautiful_cifar
* speed close to hlb_cifar
* schedule to corealize all
* one line sched step
* less lines
* add MobileNetV2 to comma CI
* symlink imagenet
* also the signature
* comment that out
* need imagenetmock
* same train and test set
* quantize on CPU=1
* verbose
* need __hexagon_divsf3
* 0x858d6c15
* quant cpu + CC=clang-19
* work on minrf example
* more
* jit sample
* t is tensor not const
* fixes
* more convs
* fix dropout
* don't print
* 504
* big patch
* onehot
* touch
* use embeddings
* dumb uses final layer
* act
* non fl
* match
* tp
* 3
* of
* ppsz
* normal
* add adln
* no t
* weird transformer
* weird transformer
* contig
* actual speed fix
* dumb
* cb
* 0
* t is 0
* mort-t
* args
* dumb days are over
* readable
* contig
* no more t mask
* mask_t
* init to zero
* clean
* steps
* work
* tt
* t
* solid
* make beautiful indexing use a Variable
* stunning test
* better color
* training is broken
* fix tests
* fix variable indexing
* fix test
* no contiguous
* revert that
* revert that too
* indexing two bind
* skip for webgpu
* make not slow
`BS=96 BASEDIR="/raid/datasets/openimages" MODEL=retinanet python examples/mlperf/model_eval.py`
```
...
loaded dataset @ 8.64s
loaded initial data @ 12.57s
****** 619.97 ms to enqueue, 46042.13 ms to realize ( 116.22 ms fetching, 45399.58 ms postprocess_detections). 0.09 examples/sec. 0.83 TFLOPS @ 59.23s
****** 147.49 ms to enqueue, 37362.16 ms to realize ( 146.96 ms fetching, 36618.84 ms postprocess_detections). 0.11 examples/sec. 1.03 TFLOPS @ 96.74s
****** 152.85 ms to enqueue, 37244.08 ms to realize ( 120.67 ms fetching, 36235.19 ms postprocess_detections). 0.11 examples/sec. 1.04 TFLOPS @ 134.14s
****** 146.39 ms to enqueue, 37279.85 ms to realize ( 65.07 ms fetching, 36233.56 ms postprocess_detections). 0.11 examples/sec. 1.04 TFLOPS @ 171.56s
****** 152.41 ms to enqueue, 37264.04 ms to realize ( 127.08 ms fetching, 36196.10 ms postprocess_detections). 0.11 examples/sec. 1.04 TFLOPS @ 208.98s
****** 151.29 ms to enqueue, 36868.08 ms to realize ( 142.73 ms fetching, 36153.07 ms postprocess_detections). 0.11 examples/sec. 1.05 TFLOPS @ 246.00s
****** 136.41 ms to enqueue, 37325.04 ms to realize ( 90.29 ms fetching, 36573.38 ms postprocess_detections). 0.11 examples/sec. 1.04 TFLOPS @ 283.46s
```
eval 35 sec -> 20 sec. it was spending 13 seconds assembling output tensor on CPU backend. GPUS[0] seems to have enough memory, otherwise we can lower EVAL_BS
