* Add a specialized kernel for copy2d.
* Move the cat operations.
* Avoid transpositions in cat.
* Bugfix.
* Bugfix for the cuda kernel.
* Add a benchmark.
* Add more testing.
* Test fix.
* Faster kernel.
* Add the missing kernel.
* Tweak the test.
* Add a metal kernel.
* Fix for the metal kernel.
* Get the tests to pass on metal.
* Also use this opportunity to fix the metal kernel for ELU.
* Add some bf16 kernels.
* Clippy fixes.
* use_resource API misunderstood. It is not additive. Several usages must be bit-ORed together.
* The seeding was incorrect and used the address instead of the value of the passed in seed.
* Add a check that likely exhibits failure to update the seed between generation of random tensors.
* Buffer overrun, the length given to the std::ptr::copy call was in bytes, and not 32-bit units.
* By default seed the RNG with a time-based value, so that different runs may produce different output, just like the CPU engine.
Use device.set_seed if determinism is warranted.
* Revert "By default seed the RNG with a time-based value, so that different runs may produce different output, just like the CPU engine. Use device.set_seed if determinism is warranted."
This reverts commit d7302de9
Discussion in https://github.com/huggingface/candle/pull/1811#issuecomment-1983079119
* The Metal random kernel failed to set element N/2 of tensors with N elements, N being even. The reason was that all threads but thread 0 all created 2 random samples, but thread 0 only one, i.e. an odd number. In order to produce an even number of samples, the early termination of thread 0 should only everr occur for odd sized tensors.
* Add a test catching any deterministic tensor element in rand and randn output.
---------
Co-authored-by: niklas <niklas@appli.se>
Co-authored-by: Ivar Flakstad <69173633+ivarflakstad@users.noreply.github.com>
* Add a couple functions required for yolo.
* Add the yolo-v3 example.
* Add minimum and maximum.
* Use the newly introduced maximum.
* Cuda support for min/max + add some testing.
* Allow for more tests to work with accelerate.
* Fix a typo.
* Change distributions
Standard generates in [0, 1), Normal is correct.
* Add test
Not sure if this is the best place to put the test
* Remove unnecessary use
* Cuda support for the mnist training.
* min/max fix + testing.
* Add the argmin/argmax tests.
* More cuda support for argmin/argmax.
* Cuda kernels for argmin and argmax.
* Cleanup some todos.
* Fix more todo.
* Optimize for the contiguous case.
* Add the IntDType trait.
* Handle the intdtype trait for more ops.
* Remove a todo.
* Remove a todo.
