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AstrAI/csrc/kernels/attn_paged_prefill.cu
T

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#include "attn_dispatchers.cuh"
#include "attn_entry_utils.cuh"
torch::Tensor attn_paged_prefill(
torch::Tensor q,
torch::Tensor k_cache,
torch::Tensor v_cache,
torch::Tensor req_to_token,
torch::Tensor req_pool_indices,
torch::Tensor kv_indptr,
torch::Tensor qo_indptr,
torch::Tensor q_tile_to_batch,
torch::Tensor q_tile_to_index,
c10::optional<torch::Tensor> mask,
int64_t causal_offset,
double scale
) {
const at::cuda::OptionalCUDAGuard device_guard(device_of(q));
auto stream = at::cuda::getCurrentCUDAStream();
AttentionParams<bf16> p;
attn_pack_paged_prefill_params(q, k_cache, v_cache,
req_to_token, req_pool_indices,
kv_indptr, qo_indptr,
q_tile_to_batch, q_tile_to_index, mask,
causal_offset, scale, p);
auto O = torch::empty({q.size(0), q.size(1), q.size(2)}, q.options());
p.o_ptr = (bf16*)O.data_ptr();
DISPATCH_HEAD_DIM(p.head_dim, dispatch_paged_prefill, p, stream);
C10_CUDA_CHECK(cudaGetLastError());
return O;
}
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("attn_paged_prefill", &attn_paged_prefill,
py::arg("q"),
py::arg("k_cache"),
py::arg("v_cache"),
py::arg("req_to_token"),
py::arg("req_pool_indices"),
py::arg("kv_indptr"),
py::arg("qo_indptr"),
py::arg("q_tile_to_batch"),
py::arg("q_tile_to_index"),
py::arg("mask") = py::none(),
py::arg("causal_offset") = -1,
py::arg("scale") = 0.0,
"SGLang-style paged prefill: flat KV pool + ragged batch.");
}