TensorRT-LLMs/cpp/tensorrt_llm/kernels/banBadWords.cu
Yihan Wang 9df4dad3b6
[None][fix] Introduce inline namespace to avoid symbol collision (#9541)
Signed-off-by: Yihan Wang <yihwang@nvidia.com>
2025-12-12 23:32:15 +08:00

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/*
* Copyright (c) 2022-2024, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "tensorrt_llm/common/config.h"
#include "tensorrt_llm/common/cudaUtils.h"
#include "tensorrt_llm/kernels/banBadWords.h"
using namespace tensorrt_llm::common;
using namespace tensorrt_llm::runtime;
TRTLLM_NAMESPACE_BEGIN
namespace kernels
{
template <typename T>
__global__ void ban_bad_words(T* logits, TokenIdType const** output_ids_ptr, SizeType32 const** parent_ids_ptr,
SizeType32 const* batch_slots, SizeType32 beam_width, TokenIdType const* const* bad_words_ptrs,
SizeType32 const* bad_words_lens, SizeType32 vocab_size_padded, SizeType32 const* sequence_lengths,
SizeType32 max_seq_len)
{
auto const id = blockIdx.x * blockDim.x + threadIdx.x;
auto const batch_idx = blockIdx.y / beam_width;
auto const beam_idx = blockIdx.y % beam_width;
auto const batch_slot = batch_slots != nullptr ? batch_slots[batch_idx] : batch_idx;
auto const batch_beam_idx = batch_slot * beam_width + beam_idx;
auto const* base_bad_words = bad_words_ptrs[batch_slot];
auto const bad_words_len = bad_words_lens[batch_slot];
auto const* base_bad_words_offsets = base_bad_words + bad_words_len;
if (id >= bad_words_len || base_bad_words_offsets[id] < 0)
{
return;
}
auto const item_end = base_bad_words_offsets[id];
auto const item_start = (id > 0) ? base_bad_words_offsets[id - 1] : 0;
auto const item_size = item_end - item_start;
/* The single-token case unconditionally bans the token */
bool should_ban = item_size == 1;
auto const current_step{sequence_lengths[batch_beam_idx]};
/* Multi-token case and enough previously generated tokens to look for a match
*/
if (item_size > 1 && current_step >= item_size - 1)
{
should_ban = true;
auto parent_id = static_cast<SizeType32>(beam_idx);
bool const gather_beam = beam_width > 1;
for (auto token_idx = item_size - 2; token_idx >= 0; token_idx--)
{
auto const previous_token
= output_ids_ptr[batch_slot][parent_id * max_seq_len + current_step - (item_size - 1) + token_idx];
if (previous_token != base_bad_words[item_start + token_idx])
{
should_ban = false;
break;
}
if (gather_beam)
{
parent_id = parent_ids_ptr == nullptr
? SizeType32{0}
: parent_ids_ptr[batch_slot][parent_id * max_seq_len + current_step - (item_size - 1) + token_idx];
if (parent_id < 0 || parent_id >= beam_width)
{
should_ban = false;
break;
}
}
}
}
if (should_ban)
{
auto banned_token = base_bad_words[item_end - 1];
if (0 <= banned_token && banned_token < vocab_size_padded)
{
logits[batch_idx * beam_width * vocab_size_padded + beam_idx * vocab_size_padded + banned_token]
= static_cast<T>(-INFINITY);
}
}
}
template <typename T>
void invokeBanBadWords(T* logits, TokenIdType const** output_ids_ptr, SizeType32 const** parent_ids_ptr,
SizeType32 const* batch_slot, SizeType32 batch_size, SizeType32 beam_width, TokenIdType const* const* bad_words,
SizeType32 const* bad_words_lens, SizeType32 max_bad_words_len, SizeType32 vocab_size_padded,
SizeType32 const* sequence_lengths, SizeType32 max_seq_len, cudaStream_t stream)
{
dim3 block, grid;
constexpr SizeType32 max_blocks{256};
block.x = min(((max_bad_words_len + 32 - 1) / 32) * 32, max_blocks);
grid.x = (max_bad_words_len + block.x - 1) / block.x;
grid.y = batch_size * beam_width;
ban_bad_words<<<grid, block, 0, stream>>>(logits, output_ids_ptr, parent_ids_ptr, batch_slot, beam_width, bad_words,
bad_words_lens, vocab_size_padded, sequence_lengths, max_seq_len);
sync_check_cuda_error(stream);
}
template void invokeBanBadWords(half* logits, TokenIdType const** output_ids_ptr, SizeType32 const** parent_ids_ptr,
SizeType32 const* batch_slot, SizeType32 batch_size, SizeType32 beam_width, TokenIdType const* const* bad_words,
SizeType32 const* bad_words_lens, SizeType32 max_bad_words_len, SizeType32 vocab_size_padded,
SizeType32 const* sequence_lengths, SizeType32 max_seq_len, cudaStream_t stream);
#ifdef ENABLE_BF16
template void invokeBanBadWords(__nv_bfloat16* logits, TokenIdType const** output_ids_ptr,
SizeType32 const** parent_ids_ptr, SizeType32 const* batch_slot, SizeType32 batch_size, SizeType32 beam_width,
TokenIdType const* const* bad_words, SizeType32 const* bad_words_lens, SizeType32 max_bad_words_len,
SizeType32 vocab_size_padded, SizeType32 const* sequence_lengths, SizeType32 max_seq_len, cudaStream_t stream);
#endif
template void invokeBanBadWords(float* logits, TokenIdType const** output_ids_ptr, SizeType32 const** parent_ids_ptr,
SizeType32 const* batch_slot, SizeType32 batch_size, SizeType32 beam_width, TokenIdType const* const* bad_words,
SizeType32 const* bad_words_lens, SizeType32 max_bad_words_len, SizeType32 vocab_size_padded,
SizeType32 const* sequence_lengths, SizeType32 max_seq_len, cudaStream_t stream);
} // namespace kernels
TRTLLM_NAMESPACE_END