56 lines
2.5 KiB
Plaintext
56 lines
2.5 KiB
Plaintext
/*
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* Copyright (c) 2025 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/scheduler.cuh>
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#include <optional>
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#include "batch_mla_config.inc"
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#include "tvm_binding_utils.h"
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using namespace flashinfer;
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IntTuple BatchMLAPagedAttentionPlan(DLTensor* float_workspace_buffer,
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DLTensor* int_workspace_buffer,
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DLTensor* page_locked_int_workspace_buffer, DLTensor* qo_indptr,
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DLTensor* kv_indptr, IntTuple kv_len_arr, int64_t num_heads,
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int64_t head_dim_o, bool causal, TVMStreamHandle cuda_stream) {
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size_t float_workspace_size_in_bytes =
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float_workspace_buffer->shape[0] * DataType(float_workspace_buffer->dtype).bytes();
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size_t int_workspace_size_in_bytes =
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int_workspace_buffer->shape[0] * DataType(int_workspace_buffer->dtype).bytes();
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std::vector<IdType> kv_len_vec{kv_len_arr->data, kv_len_arr->data + kv_len_arr->size};
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MLAPlanInfo plan_info;
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int batch_size = kv_len_vec.size();
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cudaStream_t stream = static_cast<cudaStream_t>(cuda_stream);
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cudaError_t status = MLAPlan<IdType>(
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static_cast<char*>(float_workspace_buffer->data) + float_workspace_buffer->byte_offset,
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float_workspace_size_in_bytes,
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static_cast<char*>(int_workspace_buffer->data) + int_workspace_buffer->byte_offset,
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static_cast<char*>(page_locked_int_workspace_buffer->data) +
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page_locked_int_workspace_buffer->byte_offset,
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int_workspace_size_in_bytes, plan_info,
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static_cast<IdType*>(qo_indptr->data) + qo_indptr->byte_offset / sizeof(IdType),
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static_cast<IdType*>(kv_indptr->data) + kv_indptr->byte_offset / sizeof(IdType),
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kv_len_vec.data(), batch_size, num_heads, head_dim_o, causal, stream);
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CHECK(status == cudaSuccess) << "Failed to plan MLA, error: " << cudaGetErrorString(status);
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std::vector<int64_t> plan_info_vec = plan_info.ToVector();
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return IntTuple{plan_info_vec.begin(), plan_info_vec.end()};
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}
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