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enginex-ascend-910-vllm/csrc/kernels/get_masked_input_and_mask_kernel.cpp
2025-09-09 09:40:35 +08:00

379 lines
16 KiB
C++

/*
* Copyright (c) Huawei Technologies Co., Ltd. 2024. All rights reserved.
*/
#include "kernel_operator.h"
#include "kernel_tensor_impl.h"
#include "kernel_type.h"
#include "types.h"
#include "utils.h"
using vllm_ascend::AccType;
template<typename scalar_t>
class GetMaskedInputAndMask {
public:
__aicore__ inline GetMaskedInputAndMask() {}
__aicore__ inline ~GetMaskedInputAndMask() {
pipe.Reset();
}
__aicore__ inline void Init(
__gm__ scalar_t* input,
__gm__ scalar_t* masked_input,
__gm__ bool* mask_out,
const int64_t org_vocab_start_index,
const int64_t org_vocab_end_index,
const int64_t num_org_vocab_padding,
const int64_t added_vocab_start_index,
const int64_t added_vocab_end_index,
const int64_t size)
{
// Initialize basic parameters
input_ = input;
masked_input_ = masked_input;
mask_out_ = mask_out;
org_vocab_start_index_ = org_vocab_start_index;
org_vocab_end_index_ = org_vocab_end_index;
size_ = ((size + 31) / 32) * 32;
added_offset_ = added_vocab_start_index -
(org_vocab_end_index - org_vocab_start_index) -
num_org_vocab_padding;
added_vocab_start_index_ = added_vocab_start_index;
added_vocab_end_index_ = added_vocab_end_index;
// Initialize global tensors
inputGlobal.SetGlobalBuffer(input);
maskedOutputGlobal.SetGlobalBuffer(masked_input);
maskOutGlobal.SetGlobalBuffer(mask_out);
// Initialize queues
pipe.InitBuffer(inQueue, 1, size_ * sizeof(scalar_t));
pipe.InitBuffer(outQueue, 1, size_ * sizeof(scalar_t));
pipe.InitBuffer(maskQueue, 1, size_ * sizeof(bool));
// Initialize calculation buffers
// NOTE: calc_buf_1 and calc_buf_2 are also used for int16 casting on older archs.
pipe.InitBuffer(calc_buf_1, size_ * sizeof(float));
pipe.InitBuffer(calc_buf_2, size_ * sizeof(float));
// Initialize result queues
pipe.InitBuffer(result_ge_que, BUFFER_NUM, size_ * sizeof(float));
pipe.InitBuffer(result_le_que, BUFFER_NUM, size_ * sizeof(float));
pipe.InitBuffer(result_org_mask_que, BUFFER_NUM, size_ * sizeof(float));
pipe.InitBuffer(result_add_mask_que, BUFFER_NUM, size_ * sizeof(float));
// Initialize temporary buffers
pipe.InitBuffer(start_buf, size_ * sizeof(float));
pipe.InitBuffer(end_buf, size_ * sizeof(float));
pipe.InitBuffer(inputFloat_buf, size_ * sizeof(float)); // Also used for half intermediate in casting
pipe.InitBuffer(validOffset_buf, size_ * sizeof(float));
pipe.InitBuffer(vocabMask_buf_, size_ * sizeof(int8_t));
pipe.InitBuffer(ones_buf_, size_ * sizeof(float));
}
__aicore__ inline void Process()
{
CopyIn();
Compute();
CopyOut();
}
private:
__aicore__ inline void CopyIn()
{
AscendC::LocalTensor<scalar_t> inputLocal = inQueue.AllocTensor<scalar_t>();
AscendC::DataCopy(inputLocal, inputGlobal, size_);
inQueue.EnQue(inputLocal);
}
__aicore__ inline void CompareWithValue(
AscendC::LocalTensor<int8_t>& result,
const AscendC::LocalTensor<float>& input,
const AscendC::LocalTensor<float>& compare_value,
bool is_greater_equal) {
AscendC::LocalTensor<float> compute_buf = calc_buf_1.Get<float>();
if (is_greater_equal) {
AscendC::Max(compute_buf, input, compare_value, size_);
AscendC::Sub(compute_buf, compare_value, compute_buf, size_);
} else {
AscendC::Max(compute_buf, input, compare_value, size_);
AscendC::Sub(compute_buf, compute_buf, compare_value, size_);
}
AscendC::Abs(compute_buf, compute_buf, size_);
AscendC::Mins(compute_buf, compute_buf, MIN_ACCURACY_FP32, size_);
AscendC::Muls(compute_buf, compute_buf, MAX_MUL_1_FP32, size_);
AscendC::Muls(compute_buf, compute_buf, MAX_MUL_1_FP32, size_);
AscendC::Muls(compute_buf, compute_buf, MAX_MUL_2_FP32, size_);
AscendC::Adds(compute_buf, compute_buf, NEGATIVE_ONE_FP32, size_);
AscendC::Abs(compute_buf, compute_buf, size_);
AscendC::LocalTensor<half> compute_buf_fp16 = calc_buf_2.Get<half>();
AscendC::Cast(compute_buf_fp16, compute_buf, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(result, compute_buf_fp16, AscendC::RoundMode::CAST_NONE, size_);
}
__aicore__ inline void ComputeRangeMask(
AscendC::LocalTensor<int8_t>& range_mask,
const AscendC::LocalTensor<float>& input,
const float start_value,
const float end_value) {
AscendC::LocalTensor<float> start_value_tensor = start_buf.Get<float>();
AscendC::LocalTensor<float> end_value_tensor = end_buf.Get<float>();
AscendC::Duplicate(start_value_tensor, start_value, size_);
AscendC::Duplicate(end_value_tensor, end_value, size_);
AscendC::LocalTensor<int8_t> ge_result = result_ge_que.AllocTensor<int8_t>();
AscendC::LocalTensor<int8_t> lt_result = result_le_que.AllocTensor<int8_t>();
CompareWithValue(ge_result, start_value_tensor, input, true);
CompareWithValue(lt_result, input, end_value_tensor, false);
#if (__CCE_AICORE__ >= 220)
AscendC::And(range_mask, ge_result, lt_result, size_);
#else
{
// WORKAROUND for older arch
// No direct int8->int16 cast. Use half as intermediate.
// No direct int8 And. Use int16 And.
AscendC::LocalTensor<int16_t> ge_result_i16 = calc_buf_1.Get<int16_t>();
AscendC::LocalTensor<int16_t> lt_result_i16 = calc_buf_2.Get<int16_t>();
AscendC::LocalTensor<int16_t> range_mask_i16 = ge_result_i16;
// Use a temporary buffer for half type
AscendC::LocalTensor<half> tmp_half = inputFloat_buf.Get<half>();
// 1. Cast inputs: int8_t -> half -> int16_t
AscendC::Cast(tmp_half, ge_result, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(ge_result_i16, tmp_half, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(tmp_half, lt_result, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(lt_result_i16, tmp_half, AscendC::RoundMode::CAST_NONE, size_);
// 2. Perform And on int16_t tensors
AscendC::And(range_mask_i16, ge_result_i16, lt_result_i16, size_);
// 3. Cast result back: int16_t -> half -> int8_t
AscendC::Cast(tmp_half, range_mask_i16, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(range_mask, tmp_half, AscendC::RoundMode::CAST_NONE, size_);
}
#endif
}
__aicore__ inline void Compute() {
AscendC::LocalTensor<scalar_t> inputLocal = inQueue.DeQue<scalar_t>();
AscendC::LocalTensor<scalar_t> maskedLocal = outQueue.AllocTensor<scalar_t>();
AscendC::LocalTensor<int8_t> maskLocal = maskQueue.AllocTensor<int8_t>();
AscendC::LocalTensor<float> inputFloat = inputFloat_buf.Get<float>();
AscendC::Cast(inputFloat, inputLocal, AscendC::RoundMode::CAST_NONE, size_);
AscendC::LocalTensor<int8_t> orgVocabMask = result_org_mask_que.AllocTensor<int8_t>();
ComputeRangeMask(orgVocabMask,
inputFloat,
static_cast<float>(org_vocab_start_index_),
static_cast<float>(org_vocab_end_index_));
AscendC::LocalTensor<int8_t> addedVocabMask = result_add_mask_que.AllocTensor<int8_t>();
ComputeRangeMask(addedVocabMask,
inputFloat,
static_cast<float>(added_vocab_start_index_),
static_cast<float>(added_vocab_end_index_));
AscendC::LocalTensor<float> validOffset = validOffset_buf.Get<float>();
AscendC::LocalTensor<float> constOrgStartIndex = start_buf.Get<float>();
AscendC::Duplicate(constOrgStartIndex, float(org_vocab_start_index_), size_);
AscendC::LocalTensor<half> orgVocabMask_fp16;
AscendC::LocalTensor<float> orgVocabMask_fp32;
AscendC::Cast(orgVocabMask_fp16, orgVocabMask, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(orgVocabMask_fp32, orgVocabMask_fp16, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Mul(validOffset, constOrgStartIndex, orgVocabMask_fp32, size_);
AscendC::LocalTensor<float> addedOffset;
AscendC::LocalTensor<float> addedOffsetTensor = end_buf.Get<float>();
AscendC::Duplicate(addedOffsetTensor, float(added_offset_), size_);
AscendC::LocalTensor<half> addedVocabMask_fp16;
AscendC::LocalTensor<float> addedVocabMask_fp32;
AscendC::Cast(addedVocabMask_fp16, addedVocabMask, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(addedVocabMask_fp32, addedVocabMask_fp16, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Mul(addedOffset, addedOffsetTensor, addedVocabMask_fp32, size_);
AscendC::Add(validOffset, validOffset, addedOffset, size_);
AscendC::LocalTensor<int8_t> vocabMask = vocabMask_buf_.Get<int8_t>();
#if (__CCE_AICORE__ >= 220)
AscendC::Or(vocabMask,
orgVocabMask,
addedVocabMask,
size_);
#else
{
// WORKAROUND for older arch
// No direct int8->int16 cast. Use half as intermediate.
// No direct int8 Or. Use int16 Or.
AscendC::LocalTensor<int16_t> orgVocabMask_i16 = calc_buf_1.Get<int16_t>();
AscendC::LocalTensor<int16_t> addedVocabMask_i16 = calc_buf_2.Get<int16_t>();
AscendC::LocalTensor<int16_t> vocabMask_i16 = orgVocabMask_i16;
// Use a temporary buffer for half type. inputFloat_buf is free now.
AscendC::LocalTensor<half> tmp_half = inputFloat_buf.Get<half>();
// 1. Cast inputs: int8_t -> half -> int16_t
AscendC::Cast(tmp_half, orgVocabMask, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(orgVocabMask_i16, tmp_half, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(tmp_half, addedVocabMask, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(addedVocabMask_i16, tmp_half, AscendC::RoundMode::CAST_NONE, size_);
// 2. Perform Or on int16_t tensors
AscendC::Or(vocabMask_i16, orgVocabMask_i16, addedVocabMask_i16, size_);
// 3. Cast result back: int16_t -> half -> int8_t
AscendC::Cast(tmp_half, vocabMask_i16, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(vocabMask, tmp_half, AscendC::RoundMode::CAST_NONE, size_);
}
#endif
AscendC::Sub(inputFloat, inputFloat, validOffset, size_);
AscendC::LocalTensor<half> vocabMask_fp16;
AscendC::LocalTensor<float> vocabMask_fp32;
AscendC::Cast(vocabMask_fp16, vocabMask, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(vocabMask_fp32, vocabMask_fp16, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Mul(inputFloat, inputFloat, vocabMask_fp32, size_);
AscendC::Cast(maskedLocal, inputFloat, AscendC::RoundMode::CAST_CEIL, size_);
outQueue.EnQue(maskedLocal);
AscendC::LocalTensor<float> ones_tensor = ones_buf_.Get<float>();
AscendC::Duplicate(ones_tensor, (float)1, size_);
AscendC::LocalTensor<float> maskLocal_fp32;
AscendC::Sub(maskLocal_fp32, ones_tensor, vocabMask_fp32, size_);
AscendC::LocalTensor<half> maskLocal_fp16;
AscendC::Cast(maskLocal_fp16, maskLocal_fp32, AscendC::RoundMode::CAST_NONE, size_);
AscendC::Cast(maskLocal, maskLocal_fp16, AscendC::RoundMode::CAST_NONE, size_);
maskQueue.EnQue(maskLocal);
inQueue.FreeTensor(inputLocal);
}
__aicore__ inline void CopyOut()
{
AscendC::LocalTensor<scalar_t> maskedLocal = outQueue.DeQue<scalar_t>();
AscendC::LocalTensor<bool> maskLocal = maskQueue.DeQue<bool>();
AscendC::DataCopy(maskedOutputGlobal, maskedLocal, size_);
AscendC::DataCopy(maskOutGlobal, maskLocal, size_);
outQueue.FreeTensor(maskedLocal);
maskQueue.FreeTensor(maskLocal);
}
private:
static constexpr int32_t BUFFER_NUM = 2;
AscendC::TPipe pipe;
AscendC::TQue<AscendC::TPosition::VECIN, 1> inQueue;
AscendC::TQue<AscendC::TPosition::VECOUT, 1> outQueue, maskQueue;
AscendC::GlobalTensor<scalar_t> inputGlobal, maskedOutputGlobal;
AscendC::GlobalTensor<bool> maskOutGlobal;
AscendC::TBuf<AscendC::TPosition::VECCALC> calc_buf_1;
AscendC::TBuf<AscendC::TPosition::VECCALC> calc_buf_2;
AscendC::TQue<AscendC::QuePosition::VECOUT, BUFFER_NUM> result_ge_que;
AscendC::TQue<AscendC::QuePosition::VECOUT, BUFFER_NUM> result_le_que;
AscendC::TQue<AscendC::QuePosition::VECOUT, BUFFER_NUM> result_org_mask_que;
AscendC::TQue<AscendC::QuePosition::VECOUT, BUFFER_NUM> result_add_mask_que;
// Temporary buffers
AscendC::TBuf<AscendC::TPosition::VECCALC> start_buf;
AscendC::TBuf<AscendC::TPosition::VECCALC> end_buf;
AscendC::TBuf<AscendC::TPosition::VECCALC> inputFloat_buf;
AscendC::TBuf<AscendC::TPosition::VECCALC> validOffset_buf;
AscendC::TBuf<AscendC::TPosition::VECCALC> vocabMask_buf_;
AscendC::TBuf<AscendC::TPosition::VECCALC> ones_buf_;
__gm__ scalar_t *input_, *masked_input_;
__gm__ bool *mask_out_;
int64_t size_;
int64_t org_vocab_start_index_, org_vocab_end_index_;
int64_t added_vocab_start_index_, added_vocab_end_index_;
int64_t added_offset_;
static constexpr float MIN_ACCURACY_FP32 = 1.1754943508222875e-38;
static constexpr float MAX_MUL_1_FP32 = 1125899906842624;
static constexpr float MAX_MUL_2_FP32 = 67108864;
static constexpr float NEGATIVE_ONE_FP32 = -1.0f;
};
extern "C" __global__ __aicore__ void get_masked_input_and_mask_kernel(
__gm__ int32_t* input,
__gm__ int32_t* masked_input,
__gm__ bool* mask_out,
const int64_t org_vocab_start_index,
const int64_t org_vocab_end_index,
const int64_t num_org_vocab_padding,
const int64_t added_vocab_start_index,
const int64_t added_vocab_end_index,
const int64_t size,
const uint32_t loop_cnt,
const uint32_t aiv_num)
{
{
GetMaskedInputAndMask<int32_t> op{};
for (int64_t i = AscendC::GetBlockIdx(); i < loop_cnt; i += aiv_num) {
op.Init(input + i * size/loop_cnt,
masked_input + i * size/loop_cnt,
mask_out + i * size/loop_cnt,
org_vocab_start_index, org_vocab_end_index,
num_org_vocab_padding, added_vocab_start_index,
added_vocab_end_index, size/loop_cnt);
op.Process();
}
} // op destructor called here
}
namespace vllm_ascend {
void get_masked_input_and_mask_impl(
void* stream,
void* input,
void* masked_input,
void* mask_out,
const int64_t org_vocab_start_index,
const int64_t org_vocab_end_index,
const int64_t num_org_vocab_padding,
const int64_t added_vocab_start_index,
const int64_t added_vocab_end_index,
const int64_t size,
const uint32_t loop_cnt,
const uint32_t aiv_num)
{
get_masked_input_and_mask_kernel<<<aiv_num, nullptr, stream>>>(
static_cast<int32_t*>(input),
static_cast<int32_t*>(masked_input),
static_cast<bool*>(mask_out),
org_vocab_start_index,
org_vocab_end_index,
num_org_vocab_padding,
added_vocab_start_index,
added_vocab_end_index,
size,
loop_cnt,
aiv_num);
}
} // namespace vllm_ascend