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* 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.
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* Boilerplate for the quantized cuda support.
* More basic cuda support.
* More cuda quantization (quantize on cpu for now).
* Add the dequantization bit.
* Start adding some dedicated cuda kernels from llama.cpp.
* Move the kernel code.
* Start interfacing with the kernel.
* Tweak the kernel launch params.
* Bugfix for quantized metal.
* Fix some clippy lints.
* Tweak the launch parameters.
* Tweak cuda basics to perform a quantized matmul.
* Perform the dequantization on the cpu + use cublas for matmul.
* Add the dequantization kernel.
* Test the qmatmul.
* More kernels.
* Matmul-vec kernel.
* Add a couple kernels.
* More dequantization kernels.
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* Skeleton methods for IndexAdd/ScatterAdd.
* Add a Map2InPlace trait.
* Add the glue code for the index-add/scatter-add kernels.
* Tweak the file name: embeddings -> indexing.
* Add the cuda kernel for indexadd.
* And add the scatter-add kernels.
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This reverts commit c8459d199ddcea909f6ccd18ae4945cb19d3eb9e.
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* Boilerplate code for conv1d.
* Boilerplate code for conv1d.
* More boilerplate for conv1d.
* Conv1d work.
* Get the conv1d cuda kernel to work.
* Conv1d support when no batch dim.
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