* Optimize Tensor::new when called on nested Vec<..>.
* Improve performance.
* Similar flattening for the 4d case.
* More tweaks.
* Add some dummy test.
* Add the const-set op.
* Cuda implementation.
* Bugfix.
* Metal cleanup.
* Add the metal kernels.
* Add some testing.
* Finish the metal implementation.
* Bump the version.
* WIP: hopefully better const impl
* with GPU
* More tests on
* Reverting primitive for
* Incorporating review changes - added check elem count check in kerner, using for call strategy
* rustfmt ran
* Add gradient test for conv_transpose2d with stride of 2.
* Swap dilation and stride in ConvTranspose2D backpropagation.
Without this, a shape mismatch occurs with a stride of 2 and dilation of 1.
* Add further tests of the ConvTranspose2D gradient.
Values calculated with torch, minor numerical errors adjusted and commented.
* Add a slice_set op.
* Add some testing.
* Add the dedicated kv-cache module.
* Derive debug and clone.
* Expose more kv-cache functions.
* Return the current data when appending.
* Use the new cache in the quantized phi3 model.
* Add the cuda dequantize f16 kernels.
* Expose the cuda kernels.
* Add some testing + fix.
* Test the other cases too.
* A few more tests.
* Add an environment variable to enable the dequantize f16 + matmul behavior.
* Add the argsort cuda kernels.
* CPU version of arg-sort.
* Hook the cuda kernel + rework the cpu bits.
* Add some dedicated test.
* Working cuda kernel.
* Metal kernel.
* Metal adjustments.
* Bugfix.
* Use the fast rope in qwen.
* Rework the expert selection in qwen.
* Add the mmv kernels for smaller sizes.
* Support more mmv kernels.
* Use the new kernels.
* Fix the call.
* Silly fix.
* Improve the testing.
* Fix for dmmv.
* Add another dedicated test for the batching mmv.
* Fix for the batch dim in the quantized matmul example.
* Enable more tests on cuda.
* Add a test for qmm with a batch.
* Fix the zeros-dim test on metal.
* add the sign unary operator
* remove uneeded import
* remove uneeded import
* undo formatting
* undo formatting
* remove unnecessary redefintion
* allow gradient to flow through for sign and round
* fix cpu ops to ensure that negzero and positive zero are handled properly
* clippy fixes
* Properly avoid gradient tracking.
* Use a branchless version.
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
* Avoid copying the data on squeeze and unsqueeze.
* Fix the quantized llama example.
* Unrelated fix for the quantized stable-lm example on cuda.
* Fix for mamba on cuda (unrelated to the PR).
* first attempt
* progress
* integrate into metal backend
* finish and get test passing
* add other dtype support
* update transpose1d dtypes supported
* first pass at implementation of maxpool2d
* Add definitions for other dtypes
* add tests for other dtypes
* Cosmetic tweaks + re-enable maxpool2d tests for metal.
---------
Co-authored-by: Laurent <laurent.mazare@gmail.com>
* 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>
