115 lines
4.4 KiB
Plaintext
115 lines
4.4 KiB
Plaintext
/*
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* Copyright (c) 2023 by FlashInfer team.
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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 <flashinfer/attention/mask.cuh>
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#include <flashinfer/pos_enc.cuh>
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#include <optional>
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#include "flashinfer/fastdiv.cuh"
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#include "pytorch_extension_utils.h"
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#include "single_prefill_config.inc"
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namespace flashinfer {
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template <uint32_t HEAD_DIM_QK, uint32_t HEAD_DIM_VO, PosEncodingMode POS_ENCODING_MODE,
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bool USE_FP16_QK_REDUCTION, MaskMode MASK_MODE, typename AttentionVariant,
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typename Params>
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cudaError_t SinglePrefillWithKVCacheDispatched(Params params, typename Params::DTypeO* tmp,
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cudaStream_t stream);
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} // namespace flashinfer
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using namespace flashinfer;
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void single_prefill_with_kv_cache(at::Tensor q, at::Tensor k, at::Tensor v, at::Tensor tmp,
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at::Tensor o, std::optional<at::Tensor> maybe_lse,
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int64_t mask_mode_code, int64_t layout,
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int64_t window_left ADDITIONAL_FUNC_PARAMS) {
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auto device = q.device();
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unsigned int head_dim_qk = q.size(2);
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unsigned int kv_len, qo_len, num_kv_heads, num_qo_heads;
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QKVLayout kv_layout = static_cast<QKVLayout>(layout);
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qo_len = q.size(0);
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num_qo_heads = q.size(1);
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uint32_t q_stride_n = q.stride(0), q_stride_h = q.stride(1), k_stride_n, k_stride_h, v_stride_n,
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v_stride_h;
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if (kv_layout == QKVLayout::kNHD) {
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kv_len = k.size(0);
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num_kv_heads = k.size(1);
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k_stride_n = k.stride(0);
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k_stride_h = k.stride(1);
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v_stride_n = v.stride(0);
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v_stride_h = v.stride(1);
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} else {
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kv_len = k.size(1);
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num_kv_heads = k.size(0);
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k_stride_h = k.stride(0);
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k_stride_n = k.stride(1);
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v_stride_h = v.stride(0);
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v_stride_n = v.stride(1);
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}
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if (maybe_lse) {
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const auto& lse = *maybe_lse;
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TORCH_CHECK(lse.size(0) == qo_len, lse.size(0), q.size(0));
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TORCH_CHECK(lse.size(1) == num_qo_heads, lse.size(1), q.size(1));
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}
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const MaskMode mask_mode = static_cast<MaskMode>(mask_mode_code);
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auto q_scalar_type = q.scalar_type();
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auto kv_scalar_type = k.scalar_type();
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const c10::cuda::OptionalCUDAGuard device_guard(device);
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const cudaStream_t stream = c10::cuda::getCurrentCUDAStream();
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DISPATCH_context(
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DTypeQ, DTypeKV, DTypeO, IdType, MASK_MODE, HEAD_DIM_QK, HEAD_DIM_VO, POS_ENCODING_MODE,
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USE_SLIDING_WINDOW, USE_LOGITS_SOFT_CAP, USE_FP16_QK_REDUCTION, AttentionVariant, Params,
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[&] {
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Params params;
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params.q = static_cast<DTypeQ*>(q.data_ptr());
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params.k = static_cast<DTypeKV*>(k.data_ptr());
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params.v = static_cast<DTypeKV*>(v.data_ptr());
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params.o = static_cast<DTypeO*>(o.data_ptr());
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params.lse = maybe_lse ? static_cast<float*>(maybe_lse->data_ptr()) : nullptr;
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params.num_qo_heads = num_qo_heads;
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params.num_kv_heads = num_kv_heads;
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params.group_size = uint_fastdiv(num_qo_heads / num_kv_heads);
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params.qo_len = qo_len;
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params.kv_len = kv_len;
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params.q_stride_n = q_stride_n;
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params.q_stride_h = q_stride_h;
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params.k_stride_n = k_stride_n;
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params.k_stride_h = k_stride_h;
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params.v_stride_n = v_stride_n;
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params.v_stride_h = v_stride_h;
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params.window_left = window_left;
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params.partition_kv = false;
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ADDITIONAL_PARAMS_SETTER
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cudaError_t status = flashinfer::SinglePrefillWithKVCacheDispatched<
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HEAD_DIM_QK, HEAD_DIM_VO, POS_ENCODING_MODE,
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/*use_fp16_qk_reduction=*/USE_FP16_QK_REDUCTION, MASK_MODE, AttentionVariant>(
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params, static_cast<DTypeO*>(tmp.data_ptr()), stream);
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TORCH_CHECK(status == cudaSuccess,
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"SinglePrefillWithKVCache kernel launch failed, error: " +
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std::string(cudaGetErrorString(status)));
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return true;
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});
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}
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