disk tensor load contains big offset and is not meant to be run by gpu.
repro steps
```
time ./extra/optimization/generate_dataset.sh
gzip /tmp/sops
mv /tmp/sops.gz extra/datasets/
```
* add name support
* use fetch in gpt2
* remove requests from main lib, networkx also optional
* umm, keep that assert
* updates to fetch
* i love the walrus so much
* stop bundling mnist with tinygrad
* err, https
* download cache names
* add DOWNLOAD_CACHE_VERSION
* need env.
* ugh, wrong path
* replace get_child
* beautiful mnist
* beautiful mnist example
* from tinygrad import Tensor
* more beautiful
* the jit is super core tinygrad
* globalcounters reset on jit run
* symlinks and exclude
* beautiful_cartpole
* evaluate is it's own function
* no symlinks
* more beautiful
* jit reset for double speed
* type hinting for JIT
* beautiful_mnist gets 98%
* beautiful_mnist < 4s with BEAM=2
* better cartpole
* use actor critic
* zero_grad got lost
* delete double relu
* stable cartpole with PPO
* beautiful_cartpole is more beautiful
* REPLAY_BUFFER
* beautiful stuff typechecks
* None support in shape
* hp tuning
* 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
* Rename in files
* Move files
* Moved to extra/datasets as suggested
* Changes to files
* Fixed stupid mistake
---------
Co-authored-by: terafo <terafo@protonmail.com>
