* Link with cuDNN
* Initial implementation
* Remove backend apis
* Fix recording cudnn conv
* More unused backend apis
* Fix C++ conv tests
* include cudnn as python dep
* Install libcudnn9-dev-cuda-12 in CI
* cudnn only accepts contiguous inputs
* Switch to backend apis
* Plan needs to be kept alive
* Turn off tf32
* Add cache
* Test the native cuda graph api
* Set cudnn stream before execution
* Make LRUCache more like a normal container
* Do error check for cublas handle
* Zero-initilizing array
* Use tf32 for conv
* Skip TestConv.test_torch_conv_2D test
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Co-authored-by: Awni Hannun <awni@apple.com>
* Do vectorized store/load in unary ops
* Do vectorized store/load in binary_two ops
* Do vectorized store/load in copy ops
* Do vectorized store/load in ternary ops
* Use int32_t for IdxT
* binary => binary_two in binary_two.cu
* Fix tests on large arrays
* Use uint as index type
* Contig uses uint as index and non-contig uses int
* Make max op NaN propagation rules align with numpy
* Adding benchmarks and testing for max op nanpropagation
* Pre-commit formatting
* Fix max complex64 nan propagation and add test
* Improve the cpp unittest
* Only check nans on non-integral types in simd_reduce_impl.
* Cleanup using namespace alias
* Add cpu Max nanpropagation. Fix a small fib in cpu max dispatch data types for int8/int16.
* Make the max nanpropagation test more meaningful for integer types
* Remove tuple unpacking syntax to comply with earlier python versions. Add cuda skip to nanpropagation tests, fix cuda implementation in a separate PR.
* cuda graph prototype
fix signal bug + start to add dependencies
capture more
capture more ops
remaining ops
fix reduce and rope deps
add concurrent context
try update, but not working
cosistent topology order
use node api
use node api directly to reduce overhead
fix bug
use kernels in unary
cache graph
format
fix synchronization
format
* comment
