0e3f06fe9c
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com> Co-authored-by: Yuan Zhou <yuan.zhou@intel.com>
74 lines
1.8 KiB
C++
74 lines
1.8 KiB
C++
#include "cache.h"
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#include "cuda_utils.h"
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#include "ops.h"
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#include <torch/extension.h>
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
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// vLLM custom ops
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pybind11::module ops = m.def_submodule("ops", "vLLM custom operators");
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// Attention ops
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ops.def(
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"paged_attention_v1",
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&paged_attention_v1,
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"Compute the attention between an input query and the cached keys/values using PagedAttention.");
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ops.def(
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"paged_attention_v2",
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&paged_attention_v2,
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"PagedAttention V2.");
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// Activation ops
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ops.def(
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"silu_and_mul",
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&silu_and_mul,
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"Activation function used in SwiGLU.");
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ops.def(
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"gelu_and_mul",
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&gelu_and_mul,
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"Activation function used in GeGLU with `none` approximation.");
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ops.def(
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"gelu_tanh_and_mul",
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&gelu_tanh_and_mul,
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"Activation function used in GeGLU with `tanh` approximation.");
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ops.def(
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"gelu_new",
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&gelu_new,
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"GELU implementation used in GPT-2.");
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ops.def(
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"gelu_fast",
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&gelu_fast,
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"Approximate GELU implementation.");
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// Layernorm
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ops.def(
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"rms_norm",
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&rms_norm,
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"Apply Root Mean Square (RMS) Normalization to the input tensor.");
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ops.def(
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"fused_add_rms_norm",
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&fused_add_rms_norm,
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"In-place fused Add and RMS Normalization");
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// Rotary embedding
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ops.def(
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"rotary_embedding",
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&rotary_embedding,
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"Apply GPT-NeoX or GPT-J style rotary embedding to query and key");
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// Cache ops
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pybind11::module cache_ops = m.def_submodule("cache_ops", "vLLM cache ops");
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cache_ops.def(
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"swap_blocks",
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&swap_blocks,
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"Swap in (out) the cache blocks from src to dst");
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cache_ops.def(
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"copy_blocks",
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©_blocks,
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"Copy the cache blocks from src to dst");
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cache_ops.def(
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"reshape_and_cache",
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&reshape_and_cache,
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"Reshape the key and value tensors and cache them");
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}
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