mirror of
https://github.com/tinygrad/tinygrad.git
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6480a1a180* add disk_tensor * fix jit * new baseline before whitening * whitening through torch * whiting done currently at 91.65% * 91.99% * clean up mixup and 92.3% * clean up 92.30% * 92.49% before searching for new hyper-parameters * fix CI * fix white space * add whitening init in test * refactor, update hyperpara, 92.72% * converting whiting to tinygrad operation * update CI kernels count for CIFAR * add pad reflect * add random crop 92.53% * update hyperpara 93% * 93.15% on docker container, need to refactor the assignment for hyper param * print out weights and bias to be separated * bias/non-bias params separated * fix whitespace * clean up * refactor hyper-param with dict * refactor lr schedular params * fix whitespace * fix cross entropy loss * fix whitespace * move opt hyp to hyp dict * minor fixup * adjust model, loss scaling * 92.74% while using half of compute as before * update hyp for cutmix * random shuffle during batches * clean up * updating the model * update ConvGroup * disable gradients for batchnorm layer weights * whitespace * 93.92% * clean up * finally 94%git add .! * rewrite whitening to remove dependency on torch * whitespace * remove dependency on torch, 93.91% * back to 94.03% * clean up * update test_real_world |
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| .. | ||
| mnist | ||
| __init__.py | ||
| coco.py | ||
| imagenet.py | ||
| imagenet_download.py | ||
| kits19.py | ||
| librispeech.py | ||
| openimages.py | ||
| preprocess_imagenet.py | ||
| squad.py | ||