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587d063e6d
* Update TensorRT-LLM --------- Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
114 lines
5.5 KiB
Plaintext
114 lines
5.5 KiB
Plaintext
/*
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* Copyright (c) 2020-2023, NVIDIA CORPORATION. All rights reserved.
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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 "tensorrt_llm/kernels/decoderMaskedMultiheadAttention.h"
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#include <assert.h>
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#include <float.h>
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#include <type_traits>
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namespace tensorrt_llm
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{
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namespace kernels
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{
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namespace mmha
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{
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Forward declaration of the kernel launcher to avoid including decoderMaskedMultiheadAttentionLaunch.h
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template <typename T, typename KVCacheBuffer, typename T_PARAMS, int Dh>
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void mmha_launch_kernel(const T_PARAMS& params, const KVCacheBuffer& kv_cache_buffer, const cudaStream_t& stream);
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} // namespace mmha
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namespace
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{
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#define MMHA_LAUNCH_KERNEL(Dh) \
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, Dh>(params, kv_cache_buffer, stream); \
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break;
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template <typename T, typename KVCacheBuffer, typename KERNEL_PARAMS_TYPE>
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void multihead_attention_(
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const KERNEL_PARAMS_TYPE& params, const KVCacheBuffer& kv_cache_buffer, const cudaStream_t& stream)
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{
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switch (params.hidden_size_per_head)
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{
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case 32: mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 32>(params, kv_cache_buffer, stream); break;
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case 64: mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 64>(params, kv_cache_buffer, stream); break;
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case 128:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 128>(params, kv_cache_buffer, stream);
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break;
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case 256:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 256>(params, kv_cache_buffer, stream);
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break;
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#ifndef FAST_BUILD // skip mmha 48, 80, 96, 112, 144, 160, 192 and 224 for fast build
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case 48: mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 48>(params, kv_cache_buffer, stream); break;
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case 80: mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 80>(params, kv_cache_buffer, stream); break;
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case 96: mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 96>(params, kv_cache_buffer, stream); break;
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case 112:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 112>(params, kv_cache_buffer, stream);
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break;
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case 144:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 144>(params, kv_cache_buffer, stream);
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break;
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case 160:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 160>(params, kv_cache_buffer, stream);
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break;
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case 192:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 192>(params, kv_cache_buffer, stream);
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break;
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case 224:
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mmha::mmha_launch_kernel<T, KVCacheBuffer, KERNEL_PARAMS_TYPE, 224>(params, kv_cache_buffer, stream);
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break;
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#endif // FAST_BUILD
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default: TLLM_THROW("unsupported head_size");
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}
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}
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#undef MMHA_LAUNCH_KERNEL
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} // namespace
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////////////////////////////////////////////////////////////////////////////////////////////////////
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#define INSTANTIATE_MMHA_NORMAL_AND_PAGED(T, CROSS_ATTENTION) \
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void masked_multihead_attention(const Multihead_attention_params<T, CROSS_ATTENTION>& params, \
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const KVBlockArray& kv_cache_buffer, const cudaStream_t& stream) \
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{ \
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multihead_attention_<T, KVBlockArray, Multihead_attention_params<T, CROSS_ATTENTION>>( \
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params, kv_cache_buffer, stream); \
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} \
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void masked_multihead_attention(const Multihead_attention_params<T, CROSS_ATTENTION>& params, \
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const KVLinearBuffer& kv_cache_buffer, const cudaStream_t& stream) \
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{ \
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multihead_attention_<T, KVLinearBuffer, Multihead_attention_params<T, CROSS_ATTENTION>>( \
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params, kv_cache_buffer, stream); \
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}
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INSTANTIATE_MMHA_NORMAL_AND_PAGED(float, true)
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INSTANTIATE_MMHA_NORMAL_AND_PAGED(float, false)
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INSTANTIATE_MMHA_NORMAL_AND_PAGED(uint16_t, true)
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INSTANTIATE_MMHA_NORMAL_AND_PAGED(uint16_t, false)
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#ifdef ENABLE_BF16
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INSTANTIATE_MMHA_NORMAL_AND_PAGED(__nv_bfloat16, true)
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INSTANTIATE_MMHA_NORMAL_AND_PAGED(__nv_bfloat16, false)
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#endif
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#undef INSTANTIATE_MMHA_NORMAL_AND_PAGED
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////////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace kernels
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} // namespace tensorrt_llm
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