* add and reorganize test_slice_* tests
* refactor Tensor.__getitem__()
* preliminary tests for 1) 0D tensors and 2) varargs for Tensor.zeros and Tensor.ones
* always compare shapes of the numpy arrays obtained from tinygrad and torch tensors
* add more tests for 0D support
* remove test_tensor.test_slicing(). All slicing tests at test/test_ops.py
* add zero-dim support
* make test_end2end.py consistent with 0dim support
* add test for tensor with zero in shape
* don't simplify ones if shape is ()
* skip tests that need zero-size tensor support.
- zero-size tensor support not related to 0dim tensors.
* add tests for __getitem__() supporting strides >= 1
* refactor __getitem__: support for strides >= 1
* minor refactors and add comments to __getitem__
* add tests for slices with negative steps
* add support for slices with negative strides
* added kaiming_uniform init for conv2d and linear layers
* fix: set getattr
* up
* fix: set getattr
* fix comments
* better does not mean it is good
* more nonlinearities
* added test
checks the distribution of default relu option
* prettier
* fix kernel size
* edit distribution of returned tensor
* complete tests and fix fan_mode
* added higher dim test
* prettier test
* fix silly blank
* just leaky_relu mode
* default fan in and leaky relu
* update params
* fix test
* shorter
* generalize Tensor.uniform and adjust kaiming init
- added low and high parameters to Tensor.uniform function, so it can have a specific range (default is 0 to 1)
- adjusted return line of kaiming_uniform
* range from -1 to 1
* delete comment
* adjusted test_uniform
* fixed
* delete comment
* Add ResNet inference test and cannon
* Test with ResNet50
* test_car works with resnet fix
* Add KiTS19 dataset
* KiTS19: Implement iterate
* No batch load for this dataset
* Save results on iterate
* Implement dice score
* Add data prep and eval functions
* Resolve shape issue
* Conversion works but wrong values
* Segfaults when load_from_pretrained is called
* Fix segfault and assign properly
* Final result generated, though very slow
* Store and load final result to save time
* Fix typo in finalize
* Score computes
* More bug fixes, dice score is very low
* Working broken code
* Assign output values to result
* Getting a much higher score now
* Fix dataset preprocessing
* Mean DICE score of 88.5
* Ugh, typo
* Attempt to reimplement model
* Rename layers
* Tiny model works, kinda
* Accuracy? gone
* Implement InstanceNorm and match torch
* Test instance norm 2d and 3d
* Combined input block with downsample block
* Tiny model works, support strided convtranspose
* Commands to download dataset
* Clean up a bit
* unet3d_v2 -> unet3d
* Remove duplicated code
* Oops, put tests back
* feat: promote Embedding to nn
* fix: fix failing test
* feat: add test with jit
* feat: rewrite embedding to no longer need stacked for loops
* clean+fix: don't know how that happened
* e2e testing
* min failure
* no affine on bn, still fails
* why did i think i could detach that?
* allow more kernels for bn
* some test issue i don't understand
* fix binop, other tests failure
* that was a bad idea
* better layernorm
* inference kernel count tests
* new style reshape pushing
* fixup replacement
* 199 kernels is okay. fix flops
* push reshape through unaryops only
* GRAPH=2 draws the phantom ops
* found resnet issue
* non working test
* mul is cheaper than div
* OPT inflation
* SHUFFLE_PAD_OPS in OPT=2
* linearizer outputs something
* working ish
* cstyle codegen
* clang mostly works
* fix load valid
* fix numberless loop
* fancy gen
* working
* fix enet compiler
* cleanups
* float4 upcasting
* less lines
* supports_float4
* constant folding
* mulacc
* internet tests flaky in CI
* 90% image support
* fix image generic
* bugs exposed with shapetracker and single view
* new llvm
* use vload, remove OLD
* that's really poorly done
* ending up being more lines
* runs one metal kernel
* conv2d works
* ops tests are passing
* const folding
* all ops work
* pre commit always passes
* torch works
* working still
* fix graph test
* tests passing
* image almost works
* image conv works
* most images
* fix custom
* fix assignment
* fix compile enet
* clean up comments
* fix realize return value
* include shapetracker in LB repr
* copy should make a copy
* reenable method cache
* fix lna
* dtypes in graph
* forward only for IMAGE=2
* simple realize
* getting close
* fixup new api, it's good except the kernel count
* back to 197 kernels
* tests should pass
* go to a real float
* no type_on_cpu
* fix the docs
* put shapetracker back in it's proper place
* simple convnext implementation
* shorter function names
* need to realize the random functions now
* creating an optimizer realizes all params
* assign contiguous
* fix lazy lazy
* why was i doing that...add convnext to tests
* LazyNumpyArray
* enable assert + comment
* no two tiny
