47 lines
1.9 KiB
C++
47 lines
1.9 KiB
C++
/* Copyright 2025 SGLang Team. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <torch/all.h>
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#include <torch/library.h>
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#include "sgl_kernel_ops.h"
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TORCH_LIBRARY_FRAGMENT(sgl_kernel, m) {
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/*
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* From FlashMLA
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*/
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m.def(
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"get_mla_decoding_metadata(Tensor seqlens_k, int num_q_tokens_per_head_k, int h_k, int? h_q, bool "
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"is_fp8_kvcache, int? topk) -> Tensor[]");
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m.impl("get_mla_decoding_metadata", torch::kCUDA, &get_mla_decoding_metadata);
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m.def(
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"fwd_kvcache_mla(Tensor q, Tensor kv_cache, int head_size_v, Tensor seqlens_k, Tensor block_table, float "
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"softmax_scale, bool is_causal, Tensor tile_scheduler_metadata, Tensor num_splits, bool is_fp8, Tensor? indices) "
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"-> Tensor[]");
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m.impl("fwd_kvcache_mla", torch::kCUDA, &fwd_kvcache_mla);
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m.def(
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"dense_prefill_fwd(Tensor workspace_buffer, Tensor q, Tensor k, Tensor v, Tensor cumulative_seqlen_q, Tensor "
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"cumulative_seqlen_kv, Tensor o, Tensor lse, int mask_mode_code, float softmax_scale, int max_seqlen_q, int "
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"max_seqlen_kv, bool is_varlen) -> ()");
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m.impl("dense_prefill_fwd", torch::kCUDA, &FMHACutlassSM100FwdRun);
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m.def("sparse_prefill_fwd(Tensor q, Tensor kv, Tensor indices, float sm_scale, int d_v) -> Tensor[]");
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m.impl("sparse_prefill_fwd", torch::kCUDA, &sparse_prefill_fwd);
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}
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REGISTER_EXTENSION(flashmla_ops)
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