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https://github.com/NVIDIA/TensorRT-LLM.git
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db4edea1e1
* Update TensorRT-LLM --------- Co-authored-by: Kota Tsuyuzaki <bloodeagle40234@gmail.com> Co-authored-by: Pzzzzz <hello-cd.plus@hotmail.com> Co-authored-by: Patrick Reiter Horn <patrick.horn@gmail.com>
103 lines
3.8 KiB
Plaintext
103 lines
3.8 KiB
Plaintext
/*
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* Copyright (c) 2022-2024, 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 <cuda_runtime_api.h>
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#include "buildRelativeAttentionBiasKernel.h"
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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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// refer to
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// https://github.com/NVIDIA/FasterTransformer/blob/main/src/fastertransformer/kernels/bert_preprocess_kernels.cu#L291
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template <typename T>
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__global__ void buildRelativeAttentionBias(T* relative_attention_bias, T const* relative_attention_bias_table,
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int const head_num, int const seq_len, int const num_bucket, bool const is_bidirectional, int const max_distance)
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{
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int const head_id = blockIdx.x;
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for (int seq_id = threadIdx.x; seq_id < seq_len * seq_len; seq_id += blockDim.x)
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{
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int row_id = seq_id / seq_len;
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int col_id = seq_id % seq_len;
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int relative_position = col_id - row_id;
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int relative_buckets = 0;
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int tmp_num_bucket = num_bucket;
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if (is_bidirectional)
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{
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tmp_num_bucket /= 2;
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if (relative_position > 0)
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{
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relative_buckets += tmp_num_bucket;
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}
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else
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{
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relative_position *= -1;
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}
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}
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else
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{
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relative_position = abs(relative_position);
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}
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int max_exact = tmp_num_bucket / 2;
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bool is_small = relative_position < max_exact;
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int relative_position_if_large = max_exact
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+ (int) (logf(relative_position * 1.0f / max_exact) / logf((float) max_distance / max_exact)
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* (tmp_num_bucket - max_exact));
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relative_position_if_large = min(relative_position_if_large, tmp_num_bucket - 1);
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relative_buckets += is_small ? relative_position : relative_position_if_large;
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relative_attention_bias[head_id * seq_len * seq_len + seq_id]
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= relative_attention_bias_table[head_id * num_bucket + relative_buckets];
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}
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}
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template <typename T>
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void invokeBuildRelativeAttentionBias(T* relative_attention_bias, T const* relative_attention_bias_table,
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int const head_num, int const seq_len, int const num_bucket, bool const is_bidirectional, int const max_distance,
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cudaStream_t stream)
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{
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dim3 grid(head_num);
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dim3 block(256);
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buildRelativeAttentionBias<<<grid, block, 0, stream>>>(relative_attention_bias, relative_attention_bias_table,
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head_num, seq_len, num_bucket, is_bidirectional, max_distance);
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}
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template void invokeBuildRelativeAttentionBias<float>(float* relative_attention_bias,
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float const* relative_attention_bias_table, int const head_num, int const seq_len, int const num_bucket,
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bool const is_bidirectional, int const max_distance, cudaStream_t stream);
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template void invokeBuildRelativeAttentionBias<half>(half* relative_attention_bias,
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half const* relative_attention_bias_table, int const head_num, int const seq_len, int const num_bucket,
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bool const is_bidirectional, int const max_distance, cudaStream_t stream);
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#ifdef ENABLE_BF16
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template void invokeBuildRelativeAttentionBias<__nv_bfloat16>(__nv_bfloat16* relative_attention_bias,
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__nv_bfloat16 const* relative_attention_bias_table, int const head_num, int const seq_len, int const num_bucket,
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bool const is_bidirectional, int const max_distance, cudaStream_t stream);
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#endif
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} // namespace kernels
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} // namespace tensorrt_llm
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