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enginex-ascend-910-vllm/csrc/moe/causal_conv1d/op_kernel/causal_conv1d.h
Sun Ruoxi 7f8a1b1f7a init v0.23.0
Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>
2026-08-27 15:11:51 +08:00

1089 lines
45 KiB
C++

/**
* This program is free software, you can redistribute it and/or modify it.
* Copyright (c) 2025 Huawei Technologies Co., Ltd.
* This file is a part of the CANN Open Software.
* Licensed under CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING
* BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
/*!
* \file causal_conv1d.h
*/
#ifndef CAUSAL_CONV1D_H
#define CAUSAL_CONV1D_H
#include "kernel_operator.h"
#include "kernel_tiling/kernel_tiling.h"
#include "causal_conv1d_tiling_data.h"
#include "causal_conv1d_tiling_key.h"
#include "causal_conv1d_common.h"
#if defined(__CCE_AICORE__) && __CCE_AICORE__ == 310
#include "arch35/causal_conv1d_regbase.h"
#endif
namespace NsCausalConv1d {
using namespace AscendC;
using namespace NsCausalConv1dCommon;
#define CAUSAL_CONV1D_TEMPLATE_ARGS typename T, uint32_t runModeKey, uint32_t widthKey, uint32_t fnPlanKey
#define CAUSAL_CONV1D_CLASS CausalConv1d<T, runModeKey, widthKey, fnPlanKey>
enum SeqTaskWindowMode : int32_t {
SEQ_TASK_WINDOW_MODE_VARLEN = 0,
SEQ_TASK_WINDOW_MODE_BATCH = 1,
SEQ_TASK_WINDOW_MODE_DECODE2D = 2,
};
inline constexpr int32_t INIT_STATE_SYNCALL_NEED_SIZE = 8;
inline constexpr int32_t INIT_STATE_SYNCALL_MAX_BLOCKS = 64;
inline constexpr int64_t INT32_MAX_VALUE = 2147483647LL;
struct SeqTaskWindow {
bool valid = false;
int32_t start = 0;
int32_t len = 0;
};
__aicore__ inline int32_t GetSeqTaskWindowMode(int32_t inputMode)
{
if (inputMode == 0) {
return SEQ_TASK_WINDOW_MODE_VARLEN;
}
if (inputMode == 2) {
return SEQ_TASK_WINDOW_MODE_DECODE2D;
}
return SEQ_TASK_WINDOW_MODE_BATCH;
}
__aicore__ inline SeqTaskWindow BuildSeqTaskWindowVarlen(int32_t startVal, int32_t endVal)
{
SeqTaskWindow window;
window.start = startVal;
window.len = endVal - startVal;
window.valid = (window.len > 0);
return window;
}
__aicore__ inline int32_t RetreatRingSlot(int32_t slot, int32_t delta)
{
int32_t prev = slot - delta;
return (prev >= 0) ? prev : (prev + RING_SLOTS);
}
__aicore__ inline SeqTaskWindow BuildSeqTaskWindowBatch(int32_t seq, int32_t seqLen)
{
SeqTaskWindow window;
window.start = seq * seqLen;
window.len = seqLen;
window.valid = (window.len > 0);
return window;
}
__aicore__ inline SeqTaskWindow BuildSeqTaskWindowDecode2D(int32_t seq)
{
SeqTaskWindow window;
window.valid = true;
window.start = seq;
window.len = 1;
return window;
}
__aicore__ inline constexpr int32_t DecodeWidthTplKey(uint32_t widthKey)
{
switch (widthKey) {
case CAUSAL_CONV1D_TPL_WIDTH_2:
return 2;
case CAUSAL_CONV1D_TPL_WIDTH_3:
return 3;
case CAUSAL_CONV1D_TPL_WIDTH_4:
return 4;
default:
return 0;
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
class CausalConv1d {
public:
__aicore__ inline CausalConv1d() = default;
protected:
static constexpr bool kIsUpdateMode = (runModeKey == CAUSAL_CONV1D_TPL_RUN_MODE_UPDATE);
static constexpr int32_t kTemplateWidth = DecodeWidthTplKey(widthKey);
static constexpr bool kHasCompileTimeWidth =
(runModeKey == CAUSAL_CONV1D_TPL_RUN_MODE_FN) && (kTemplateWidth >= 2) && (kTemplateWidth <= MAX_WIDTH);
static constexpr FnExecutionPlan kFnExecutionPlan = static_cast<FnExecutionPlan>(fnPlanKey);
__aicore__ inline void ResetRuntimeState(const CausalConv1dTilingData *tilingData);
__aicore__ inline void InitSharedBuffersAndEvents();
__aicore__ inline void LoadWeightAndBias(int32_t channelStart, int32_t baseDim);
__aicore__ inline void InitRing(int32_t cacheIdx, bool hasInit, int32_t stateTokenOffset, int32_t start,
int32_t len, int32_t channelStart, int32_t baseDim, int32_t dim);
__aicore__ inline void InitRingSeqSplit(int32_t seq, int32_t cacheIdx, bool hasInit, int32_t seqStart,
int32_t tileStart, int32_t tileLen, int32_t channelStart, int32_t baseDim,
int32_t dim);
__aicore__ inline void PrefetchInitStatesToWorkspace(int32_t channelStart, int32_t baseDimSize);
__aicore__ inline void RestoreFnLocalPartials(int32_t baseDim);
__aicore__ inline void ComputeFnRollingOutput(int32_t slotCurr, int32_t baseDim);
__aicore__ inline void AdvanceFnLocalPartials(int32_t slotCurr, int32_t baseDim);
__aicore__ inline void RunSeqFnRolling(int32_t start, int32_t len, int32_t channelStart, int32_t baseDim,
int32_t dim);
__aicore__ inline void RunSeq(int32_t start, int32_t len, int32_t channelStart, int32_t baseDim, int32_t dim);
__aicore__ inline void WriteBackState(int32_t cacheIdx, int32_t len, int32_t channelStart, int32_t baseDim,
int32_t dim);
__aicore__ inline void WriteBackStateSpec(int32_t cacheIdx, bool hasInit, int32_t stateTokenOffset, int32_t start,
int32_t len, int32_t channelStart, int32_t baseDim, int32_t dim);
__aicore__ inline void DrainTaskMte3();
__aicore__ inline void AllocEvents();
__aicore__ inline void ReleaseEvents();
__aicore__ inline int32_t FindVarlenSeqByToken(int32_t tokenIdx) const;
__aicore__ inline bool ResolveExplicitTokenTileSeqRange(int32_t tokenTileId, int32_t &startSeq, int32_t &endSeq) const;
__aicore__ inline bool ResolveSeqTaskWindow(int32_t seq, int32_t inputMode, int32_t seqLen, int32_t &start,
int32_t &len) const;
template <int32_t kWindowMode>
__aicore__ inline bool ResolveSeqTaskWindowByMode(int32_t seq, int32_t seqLen, int32_t &start, int32_t &len) const;
__aicore__ inline int32_t ReadQueryStartLocValue(int32_t index) const;
__aicore__ inline int64_t ReadCacheIndexValue(int32_t seq) const;
__aicore__ inline bool ReadInitialStateModeValue(int32_t seq) const;
__aicore__ inline int32_t ReadNumAcceptedTokensValue(int32_t seq) const;
__aicore__ inline bool ResolveSeqCacheIndex(int32_t seq, bool hasCacheIndices, int32_t &cacheIdx) const;
__aicore__ inline bool ResolveSeqHasInit(int32_t seq, bool hasInitialStateMode) const;
__aicore__ inline void MaybeWriteBackSeqSplitTailChunk(int32_t chunkStart, int32_t chunkLen, int32_t seqStart,
int32_t seqLen, int32_t cacheIdx, int32_t channelStart,
int32_t baseDim, int32_t dim);
__aicore__ inline void ProcessDefault();
template <int32_t kWindowMode>
__aicore__ inline void ProcessDefaultByWindowMode();
__aicore__ inline void ProcessVarlenTokenTiled();
__aicore__ inline void ProcessFnChunk(int32_t seq, int32_t cacheIdx, bool hasInit, int32_t seqStart,
int32_t seqLen, int32_t chunkStart, int32_t chunkLen, int32_t channelStart,
int32_t baseDim, int32_t dim);
__aicore__ inline const CausalConv1dTilingData *GetTilingData() const;
__aicore__ inline bool HasActivation() const;
__aicore__ inline bool HasBias() const;
__aicore__ inline bool IsUpdateMode() const;
__aicore__ inline bool IsFnRollingFastPathEnabled() const;
__aicore__ inline bool HasExplicitFnTokenSeqRanges() const;
__aicore__ inline bool IsUpdateSpecDecodingEnabled() const;
protected:
TPipe pipe;
TBuf<QuePosition::VECIN> inBuf;
TBuf<QuePosition::VECOUT> outBuf;
TBuf<QuePosition::VECCALC> calcBuf;
TEventID weightBiasMte2ToVEvent_;
TEventID stateMte2ToVEvent_;
TEventID inputMte2ToVEvent_[RING_SLOTS];
TEventID inputVToMte2Event_;
TEventID outMte3ToVEvent_[2];
TEventID outVToMte3Event_[2];
TEventID stateWritebackMte3ToVEvent_;
TEventID stateWritebackMte3ToMte2Event_;
TEventID stateShiftMte2ToMte3Event_;
TEventID stateShiftVToMte3Event_;
TEventID stateShiftMte3ToMte2Event_;
TEventID initSnapshotMte2ToMte3Event_;
TEventID initSnapshotMte3ToMte2Event_;
TEventID initSyncVToMte3Event_;
TEventID initSyncMte3ToVEvent_;
TEventID specWritebackMte2ToMte3Event_[2];
TEventID specWritebackMte3ToMte2Event_[2];
GlobalTensor<T> xGm;
GlobalTensor<T> weightGm;
GlobalTensor<T> biasGm;
GlobalTensor<T> convStatesGm;
GlobalTensor<int32_t> queryStartLocGmInt32;
GlobalTensor<int64_t> queryStartLocGmInt64;
GlobalTensor<int32_t> cacheIndicesGmInt32;
GlobalTensor<int64_t> cacheIndicesGmInt64;
GlobalTensor<bool> initialStateModeGmBool;
GlobalTensor<int32_t> initialStateModeGmInt32;
GlobalTensor<int64_t> initialStateModeGmInt64;
GlobalTensor<int32_t> numAcceptedTokensGmInt32;
GlobalTensor<int64_t> numAcceptedTokensGmInt64;
GlobalTensor<T> yGm;
GlobalTensor<int32_t> initStateSyncGm_;
GlobalTensor<T> initStateWorkspaceGm_;
const CausalConv1dTilingData *tilingData_{nullptr};
};
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::ResetRuntimeState(const CausalConv1dTilingData *tilingData)
{
tilingData_ = tilingData;
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::InitSharedBuffersAndEvents()
{
pipe.InitBuffer(inBuf, RING_SLOTS * MAX_BLOCK_DIM * sizeof(T));
pipe.InitBuffer(outBuf, 2 * MAX_BLOCK_DIM * sizeof(T));
pipe.InitBuffer(calcBuf, (MAX_WIDTH + 4) * MAX_BLOCK_DIM * sizeof(float));
AllocEvents();
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::AllocEvents()
{
weightBiasMte2ToVEvent_ = GetTPipePtr()->AllocEventID<HardEvent::MTE2_V>();
stateMte2ToVEvent_ = GetTPipePtr()->AllocEventID<HardEvent::MTE2_V>();
for (int32_t i = 0; i < RING_SLOTS; ++i) {
inputMte2ToVEvent_[i] = GetTPipePtr()->AllocEventID<HardEvent::MTE2_V>();
}
inputVToMte2Event_ = GetTPipePtr()->AllocEventID<HardEvent::V_MTE2>();
outMte3ToVEvent_[0] = GetTPipePtr()->AllocEventID<HardEvent::MTE3_V>();
outMte3ToVEvent_[1] = GetTPipePtr()->AllocEventID<HardEvent::MTE3_V>();
outVToMte3Event_[0] = GetTPipePtr()->AllocEventID<HardEvent::V_MTE3>();
outVToMte3Event_[1] = GetTPipePtr()->AllocEventID<HardEvent::V_MTE3>();
stateWritebackMte3ToVEvent_ = GetTPipePtr()->AllocEventID<HardEvent::MTE3_V>();
stateWritebackMte3ToMte2Event_ = GetTPipePtr()->AllocEventID<HardEvent::MTE3_MTE2>();
stateShiftMte2ToMte3Event_ = GetTPipePtr()->AllocEventID<HardEvent::MTE2_MTE3>();
stateShiftVToMte3Event_ = GetTPipePtr()->AllocEventID<HardEvent::V_MTE3>();
stateShiftMte3ToMte2Event_ = GetTPipePtr()->AllocEventID<HardEvent::MTE3_MTE2>();
initSnapshotMte2ToMte3Event_ = GetTPipePtr()->AllocEventID<HardEvent::MTE2_MTE3>();
initSnapshotMte3ToMte2Event_ = GetTPipePtr()->AllocEventID<HardEvent::MTE3_MTE2>();
initSyncVToMte3Event_ = GetTPipePtr()->AllocEventID<HardEvent::V_MTE3>();
initSyncMte3ToVEvent_ = GetTPipePtr()->AllocEventID<HardEvent::MTE3_V>();
specWritebackMte2ToMte3Event_[0] = GetTPipePtr()->AllocEventID<HardEvent::MTE2_MTE3>();
specWritebackMte2ToMte3Event_[1] = GetTPipePtr()->AllocEventID<HardEvent::MTE2_MTE3>();
specWritebackMte3ToMte2Event_[0] = GetTPipePtr()->AllocEventID<HardEvent::MTE3_MTE2>();
specWritebackMte3ToMte2Event_[1] = GetTPipePtr()->AllocEventID<HardEvent::MTE3_MTE2>();
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::ReleaseEvents()
{
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_V>(weightBiasMte2ToVEvent_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_V>(stateMte2ToVEvent_);
for (int32_t i = 0; i < RING_SLOTS; ++i) {
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_V>(inputMte2ToVEvent_[i]);
}
GetTPipePtr()->ReleaseEventID<HardEvent::V_MTE2>(inputVToMte2Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_V>(outMte3ToVEvent_[0]);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_V>(outMte3ToVEvent_[1]);
GetTPipePtr()->ReleaseEventID<HardEvent::V_MTE3>(outVToMte3Event_[0]);
GetTPipePtr()->ReleaseEventID<HardEvent::V_MTE3>(outVToMte3Event_[1]);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_V>(stateWritebackMte3ToVEvent_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_MTE2>(stateWritebackMte3ToMte2Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_MTE3>(stateShiftMte2ToMte3Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::V_MTE3>(stateShiftVToMte3Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_MTE2>(stateShiftMte3ToMte2Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_MTE3>(initSnapshotMte2ToMte3Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_MTE2>(initSnapshotMte3ToMte2Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::V_MTE3>(initSyncVToMte3Event_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_V>(initSyncMte3ToVEvent_);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_MTE3>(specWritebackMte2ToMte3Event_[0]);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE2_MTE3>(specWritebackMte2ToMte3Event_[1]);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_MTE2>(specWritebackMte3ToMte2Event_[0]);
GetTPipePtr()->ReleaseEventID<HardEvent::MTE3_MTE2>(specWritebackMte3ToMte2Event_[1]);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::LoadWeightAndBias(int32_t channelStart, int32_t baseDim)
{
const int32_t dim = tilingData_->dim;
const int32_t width = static_cast<int32_t>(tilingData_->width);
const int32_t jStart = MAX_WIDTH - width;
const bool hasBias = HasBias();
auto cl = CalcBufLayout::FromCalcBuf(calcBuf);
LocalTensor<float> &weightF = cl.weightF;
LocalTensor<float> &biasF = cl.biasF;
LocalTensor<T> weightT;
LocalTensor<T> biasT;
if constexpr (!std::is_same<T, float>::value) {
weightT = weightF.ReinterpretCast<T>();
biasT = biasF.ReinterpretCast<T>();
}
for (int32_t j = 0; j < jStart; ++j) {
Duplicate(weightF[j * MAX_BLOCK_DIM], 0.0f, baseDim);
}
for (int32_t j = 0; j < width; ++j) {
const int32_t jDst = jStart + j;
const int64_t weightOffset = static_cast<int64_t>(j) * dim + channelStart;
if constexpr (std::is_same<T, float>::value) {
DataCopy(weightF[jDst * MAX_BLOCK_DIM], weightGm[weightOffset], baseDim);
} else {
DataCopy(weightT[jDst * MAX_BLOCK_DIM * 2 + MAX_BLOCK_DIM], weightGm[weightOffset], baseDim);
}
}
if (hasBias) {
if constexpr (std::is_same<T, float>::value) {
DataCopy(biasF, biasGm[channelStart], baseDim);
} else {
DataCopy(biasT[MAX_BLOCK_DIM], biasGm[channelStart], baseDim);
}
}
SetFlag<HardEvent::MTE2_V>(weightBiasMte2ToVEvent_);
WaitFlag<HardEvent::MTE2_V>(weightBiasMte2ToVEvent_);
if constexpr (!std::is_same<T, float>::value) {
for (int32_t j = 0; j < width; ++j) {
const int32_t jDst = jStart + j;
Cast(weightF[jDst * MAX_BLOCK_DIM], weightT[jDst * MAX_BLOCK_DIM * 2 + MAX_BLOCK_DIM], RoundMode::CAST_NONE,
baseDim);
}
if (hasBias) {
Cast(biasF, biasT[MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
}
PipeBarrier<PIPE_V>();
}
if (!hasBias) {
Duplicate(biasF, 0.0f, baseDim);
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::InitRing(int32_t cacheIdx, bool hasInit, int32_t stateTokenOffset,
int32_t start, int32_t len, int32_t channelStart,
int32_t baseDim, int32_t dim)
{
const int32_t stateLen = tilingData_->stateLen;
const int32_t width = static_cast<int32_t>(tilingData_->width);
const int32_t ringStart = MAX_WIDTH - width;
LocalTensor<T> ring = inBuf.Get<T>();
for (int32_t i = 0; i < ringStart; ++i) {
Duplicate(ring[i * MAX_BLOCK_DIM], static_cast<T>(0), baseDim);
}
if (ringStart > 0) {
PipeBarrier<PIPE_V>();
}
if (hasInit) {
for (int32_t i = 0; i < (width - 1); ++i) {
const int32_t pos = stateTokenOffset + i;
const int64_t stateOffset =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(pos) * dim + channelStart;
DataCopy(ring[(ringStart + i) * MAX_BLOCK_DIM], convStatesGm[stateOffset], baseDim);
}
SetFlag<HardEvent::MTE2_V>(stateMte2ToVEvent_);
WaitFlag<HardEvent::MTE2_V>(stateMte2ToVEvent_);
} else {
for (int32_t i = 0; i < (width - 1); ++i) {
Duplicate(ring[(ringStart + i) * MAX_BLOCK_DIM], static_cast<T>(0), baseDim);
}
PipeBarrier<PIPE_V>();
}
if (len > 0) {
const int32_t slot0 = SlotCurr(0);
const int64_t xOffset = static_cast<int64_t>(start) * dim + channelStart;
DataCopy(ring[slot0 * MAX_BLOCK_DIM], xGm[xOffset], baseDim);
SetFlag<HardEvent::MTE2_V>(inputMte2ToVEvent_[slot0]);
}
if (len > 1) {
SetFlag<HardEvent::V_MTE2>(inputVToMte2Event_);
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::RunSeq(int32_t start, int32_t len, int32_t channelStart,
int32_t baseDim, int32_t dim)
{
if (IsFnRollingFastPathEnabled()) {
RunSeqFnRolling(start, len, channelStart, baseDim, dim);
return;
}
const int32_t width = static_cast<int32_t>(tilingData_->width);
const int32_t jStart = MAX_WIDTH - width;
auto cl = CalcBufLayout::FromCalcBuf(calcBuf);
LocalTensor<float> &weightF = cl.weightF;
LocalTensor<float> &biasF = cl.biasF;
LocalTensor<float> &accF = cl.accF;
LocalTensor<float> &tmpF = cl.tmpF;
LocalTensor<T> ring = inBuf.Get<T>();
LocalTensor<T> outT = outBuf.Get<T>();
const bool hasBias = HasBias();
const bool hasActivation = HasActivation();
for (int32_t t = 0; t < len; ++t) {
const int32_t slotCurr = SlotCurr(t);
WaitFlag<HardEvent::MTE2_V>(inputMte2ToVEvent_[slotCurr]);
if (t + 1 < len) {
const int32_t slotNext = SlotPrefetch(t);
const int64_t xOffsetNext = static_cast<int64_t>(start + t + 1) * dim + channelStart;
WaitFlag<HardEvent::V_MTE2>(inputVToMte2Event_);
DataCopy(ring[slotNext * MAX_BLOCK_DIM], xGm[xOffsetNext], baseDim);
SetFlag<HardEvent::MTE2_V>(inputMte2ToVEvent_[slotNext]);
}
bool accInitialized = false;
if (hasBias) {
Adds(accF, biasF, 0.0f, baseDim);
PipeBarrier<PIPE_V>();
accInitialized = true;
}
for (int32_t j = jStart; j < MAX_WIDTH; ++j) {
const int32_t tap = (MAX_WIDTH - 1) - j;
const int32_t slot = (tap == 0) ? slotCurr : SlotHist(t, tap);
Cast(tmpF, ring[slot * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
if (!accInitialized) {
Mul(accF, tmpF, weightF[j * MAX_BLOCK_DIM], baseDim);
accInitialized = true;
} else {
MulAddDst(accF, tmpF, weightF[j * MAX_BLOCK_DIM], baseDim);
}
}
PipeBarrier<PIPE_V>();
if (hasActivation) {
Silu(tmpF, accF, baseDim);
}
const int32_t outSlot = t & 1;
LocalTensor<T> outSlotT = outT[outSlot * MAX_BLOCK_DIM];
if (t >= 2) {
WaitFlag<HardEvent::MTE3_V>(outMte3ToVEvent_[outSlot]);
}
if constexpr (IsSameType<T, float>::value) {
if (hasActivation) {
DataCopy(outSlotT, tmpF, baseDim);
} else {
DataCopy(outSlotT, accF, baseDim);
}
} else {
if (hasActivation) {
Cast(outSlotT, tmpF, RoundMode::CAST_RINT, baseDim);
} else {
Cast(outSlotT, accF, RoundMode::CAST_RINT, baseDim);
}
}
SetFlag<HardEvent::V_MTE3>(outVToMte3Event_[outSlot]);
const int64_t outOffset = static_cast<int64_t>(start + t) * dim + channelStart;
WaitFlag<HardEvent::V_MTE3>(outVToMte3Event_[outSlot]);
DataCopy(yGm[outOffset], outSlotT, baseDim);
if (t + 2 < len) {
SetFlag<HardEvent::MTE3_V>(outMte3ToVEvent_[outSlot]);
}
if (t + 2 < len) {
SetFlag<HardEvent::V_MTE2>(inputVToMte2Event_);
}
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::RestoreFnLocalPartials(int32_t baseDim)
{
if constexpr (!kHasCompileTimeWidth) {
return;
}
auto cl = CalcBufLayout::FromCalcBuf(calcBuf);
LocalTensor<float> &weightF = cl.weightF;
LocalTensor<float> &state2F = cl.biasF;
LocalTensor<float> &state1F = cl.accF;
LocalTensor<float> &state0F = cl.tmpF;
LocalTensor<float> &currF = cl.currF;
LocalTensor<T> ring = inBuf.Get<T>();
constexpr int32_t ringStart = MAX_WIDTH - kTemplateWidth;
constexpr int32_t w0Idx = MAX_WIDTH - kTemplateWidth;
if constexpr (kTemplateWidth == 2) {
Duplicate(state2F, 0.0f, baseDim);
Duplicate(state1F, 0.0f, baseDim);
PipeBarrier<PIPE_V>();
Cast(currF, ring[ringStart * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
Mul(state0F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
} else if constexpr (kTemplateWidth == 3) {
Duplicate(state2F, 0.0f, baseDim);
PipeBarrier<PIPE_V>();
Cast(currF, ring[ringStart * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
Mul(state0F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
Cast(currF, ring[(ringStart + 1) * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
Mul(state1F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
MulAddDst(state0F, currF, weightF[(w0Idx + 1) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
} else if constexpr (kTemplateWidth == 4) {
Cast(currF, ring[ringStart * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
Mul(state0F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
Cast(currF, ring[(ringStart + 1) * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
Mul(state1F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
MulAddDst(state0F, currF, weightF[(w0Idx + 1) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
Cast(currF, ring[(ringStart + 2) * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
Mul(state2F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
MulAddDst(state1F, currF, weightF[(w0Idx + 1) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
MulAddDst(state0F, currF, weightF[(w0Idx + 2) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::ComputeFnRollingOutput(int32_t slotCurr, int32_t baseDim)
{
if constexpr (!kHasCompileTimeWidth) {
return;
}
auto cl = CalcBufLayout::FromCalcBuf(calcBuf);
LocalTensor<float> &weightF = cl.weightF;
LocalTensor<float> &state0F = cl.tmpF;
LocalTensor<float> &currF = cl.currF;
LocalTensor<T> ring = inBuf.Get<T>();
#if defined(__CCE_AICORE__) && __CCE_AICORE__ == 310
const bool hasActivation = HasActivation();
if (hasActivation) {
ComputeFnRollingOutputRegbase<T, true>(ring[slotCurr * MAX_BLOCK_DIM], currF, state0F, weightF[3 * MAX_BLOCK_DIM], baseDim);
} else {
ComputeFnRollingOutputRegbase<T, false>(ring[slotCurr * MAX_BLOCK_DIM], currF, state0F, weightF[3 * MAX_BLOCK_DIM], baseDim);
}
#else
Cast(currF, ring[slotCurr * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
MulAddDst(state0F, currF, weightF[3 * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
const bool hasActivation = HasActivation();
if (hasActivation) {
PipeBarrier<PIPE_V>();
Silu(currF, state0F, baseDim);
}
#endif
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::AdvanceFnLocalPartials(int32_t slotCurr, int32_t baseDim)
{
if constexpr (!kHasCompileTimeWidth) {
return;
}
auto cl = CalcBufLayout::FromCalcBuf(calcBuf);
LocalTensor<float> &weightF = cl.weightF;
LocalTensor<float> &state2F = cl.biasF;
LocalTensor<float> &state1F = cl.accF;
LocalTensor<float> &state0F = cl.tmpF;
LocalTensor<float> &currF = cl.currF;
LocalTensor<T> ring = inBuf.Get<T>();
constexpr int32_t w0Idx = MAX_WIDTH - kTemplateWidth;
#if defined(__CCE_AICORE__) && __CCE_AICORE__ == 310
AdvanceFnLocalPartialsRegbase<T, kTemplateWidth>(ring[slotCurr * MAX_BLOCK_DIM], weightF[w0Idx * MAX_BLOCK_DIM],
state0F, state1F, state2F, baseDim, MAX_BLOCK_DIM);
#else
Cast(currF, ring[slotCurr * MAX_BLOCK_DIM], RoundMode::CAST_NONE, baseDim);
PipeBarrier<PIPE_V>();
if constexpr (kTemplateWidth == 2) {
Mul(state0F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
} else if constexpr (kTemplateWidth == 3) {
Mul(state0F, currF, weightF[(w0Idx + 1) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
Add(state0F, state0F, state1F, baseDim);
PipeBarrier<PIPE_V>();
Mul(state1F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
} else if constexpr (kTemplateWidth == 4) {
Mul(state0F, currF, weightF[(w0Idx + 2) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
Add(state0F, state0F, state1F, baseDim);
PipeBarrier<PIPE_V>();
Mul(state1F, currF, weightF[(w0Idx + 1) * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
Add(state1F, state1F, state2F, baseDim);
PipeBarrier<PIPE_V>();
Mul(state2F, currF, weightF[w0Idx * MAX_BLOCK_DIM], baseDim);
PipeBarrier<PIPE_V>();
}
#endif
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::RunSeqFnRolling(int32_t start, int32_t len, int32_t channelStart,
int32_t baseDim, int32_t dim)
{
if constexpr (!kHasCompileTimeWidth) {
return;
}
auto cl = CalcBufLayout::FromCalcBuf(calcBuf);
LocalTensor<float> &state0F = cl.tmpF;
LocalTensor<float> &currF = cl.currF;
LocalTensor<T> ring = inBuf.Get<T>();
LocalTensor<T> outT = outBuf.Get<T>();
const bool hasActivation = HasActivation();
RestoreFnLocalPartials(baseDim);
for (int32_t t = 0; t < len; ++t) {
const int32_t slotCurr = SlotCurr(t);
WaitFlag<HardEvent::MTE2_V>(inputMte2ToVEvent_[slotCurr]);
if (t + 1 < len) {
const int32_t slotNext = SlotPrefetch(t);
const int64_t xOffsetNext = static_cast<int64_t>(start + t + 1) * dim + channelStart;
WaitFlag<HardEvent::V_MTE2>(inputVToMte2Event_);
DataCopy(ring[slotNext * MAX_BLOCK_DIM], xGm[xOffsetNext], baseDim);
SetFlag<HardEvent::MTE2_V>(inputMte2ToVEvent_[slotNext]);
}
ComputeFnRollingOutput(slotCurr, baseDim);
const int32_t outSlot = t & 1;
LocalTensor<T> outSlotT = outT[outSlot * MAX_BLOCK_DIM];
if (t >= 2) {
WaitFlag<HardEvent::MTE3_V>(outMte3ToVEvent_[outSlot]);
}
if constexpr (IsSameType<T, float>::value) {
if (hasActivation) {
DataCopy(outSlotT, currF, baseDim);
} else {
DataCopy(outSlotT, state0F, baseDim);
}
} else {
if (hasActivation) {
Cast(outSlotT, currF, RoundMode::CAST_RINT, baseDim);
} else {
Cast(outSlotT, state0F, RoundMode::CAST_RINT, baseDim);
}
}
AdvanceFnLocalPartials(slotCurr, baseDim);
SetFlag<HardEvent::V_MTE3>(outVToMte3Event_[outSlot]);
const int64_t outOffset = static_cast<int64_t>(start + t) * dim + channelStart;
WaitFlag<HardEvent::V_MTE3>(outVToMte3Event_[outSlot]);
DataCopy(yGm[outOffset], outSlotT, baseDim);
if (t + 2 < len) {
SetFlag<HardEvent::MTE3_V>(outMte3ToVEvent_[outSlot]);
}
if (t + 2 < len) {
SetFlag<HardEvent::V_MTE2>(inputVToMte2Event_);
}
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::DrainTaskMte3()
{
SetFlag<HardEvent::MTE3_V>(stateWritebackMte3ToVEvent_);
WaitFlag<HardEvent::MTE3_V>(stateWritebackMte3ToVEvent_);
SetFlag<HardEvent::MTE3_MTE2>(stateWritebackMte3ToMte2Event_);
WaitFlag<HardEvent::MTE3_MTE2>(stateWritebackMte3ToMte2Event_);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::WriteBackState(int32_t cacheIdx, int32_t len, int32_t channelStart,
int32_t baseDim, int32_t dim)
{
const int32_t stateLen = tilingData_->stateLen;
const int32_t width = static_cast<int32_t>(tilingData_->width);
if (len <= 0) {
return;
}
const int32_t lastT = len - 1;
LocalTensor<T> ring = inBuf.Get<T>();
const int32_t lastSlot = SlotCurr(lastT);
const int64_t stateBaseOffset = static_cast<int64_t>(cacheIdx) * stateLen * dim + channelStart;
for (int32_t pos = 0; pos < (width - 1); ++pos) {
const int32_t tap = (width - 2) - pos;
const int32_t slot = RetreatRingSlot(lastSlot, tap);
const int64_t stateOffset = stateBaseOffset + static_cast<int64_t>(pos) * dim;
DataCopy(convStatesGm[stateOffset], ring[slot * MAX_BLOCK_DIM], baseDim);
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::WriteBackStateSpec(int32_t cacheIdx, bool hasInit,
int32_t stateTokenOffset, int32_t start, int32_t len,
int32_t channelStart, int32_t baseDim, int32_t dim)
{
const int32_t width = static_cast<int32_t>(tilingData_->width);
const int32_t stateLen = tilingData_->stateLen;
if (len <= 0) {
return;
}
if (width != 4) {
WriteBackState(cacheIdx, len, channelStart, baseDim, dim);
return;
}
constexpr int32_t keep = MAX_WIDTH - 2;
const int32_t reqStateLen = keep + len;
if (reqStateLen > stateLen) {
WriteBackState(cacheIdx, len, channelStart, baseDim, dim);
return;
}
LocalTensor<T> ring = inBuf.Get<T>();
LocalTensor<T> buf0 = ring[0 * MAX_BLOCK_DIM];
LocalTensor<T> buf1 = ring[1 * MAX_BLOCK_DIM];
if (hasInit) {
const int32_t srcPos0 = stateTokenOffset + 1;
const int32_t srcPos1 = stateTokenOffset + 2;
const int64_t srcOffset0 =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(srcPos0) * dim + channelStart;
const int64_t srcOffset1 =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(srcPos1) * dim + channelStart;
DataCopy(buf0, convStatesGm[srcOffset0], baseDim);
DataCopy(buf1, convStatesGm[srcOffset1], baseDim);
SetFlag<HardEvent::MTE2_MTE3>(stateShiftMte2ToMte3Event_);
WaitFlag<HardEvent::MTE2_MTE3>(stateShiftMte2ToMte3Event_);
const int64_t dstOffset0 =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(0) * dim + channelStart;
const int64_t dstOffset1 =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(1) * dim + channelStart;
DataCopy(convStatesGm[dstOffset0], buf0, baseDim);
DataCopy(convStatesGm[dstOffset1], buf1, baseDim);
SetFlag<HardEvent::MTE3_MTE2>(stateShiftMte3ToMte2Event_);
WaitFlag<HardEvent::MTE3_MTE2>(stateShiftMte3ToMte2Event_);
} else {
Duplicate(buf0, static_cast<T>(0), baseDim);
SetFlag<HardEvent::V_MTE3>(stateShiftVToMte3Event_);
WaitFlag<HardEvent::V_MTE3>(stateShiftVToMte3Event_);
const int64_t dstOffset0 =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(0) * dim + channelStart;
const int64_t dstOffset1 =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(1) * dim + channelStart;
DataCopy(convStatesGm[dstOffset0], buf0, baseDim);
DataCopy(convStatesGm[dstOffset1], buf0, baseDim);
SetFlag<HardEvent::MTE3_MTE2>(stateShiftMte3ToMte2Event_);
WaitFlag<HardEvent::MTE3_MTE2>(stateShiftMte3ToMte2Event_);
}
const int64_t xOffset0 = static_cast<int64_t>(start) * dim + channelStart;
DataCopy(buf0, xGm[xOffset0], baseDim);
SetFlag<HardEvent::MTE2_MTE3>(specWritebackMte2ToMte3Event_[0]);
for (int32_t t = 0; t < len; ++t) {
const int32_t curr = t & 1;
const int32_t next = curr ^ 1;
LocalTensor<T> currBuf = (curr == 0) ? buf0 : buf1;
LocalTensor<T> nextBuf = (next == 0) ? buf0 : buf1;
WaitFlag<HardEvent::MTE2_MTE3>(specWritebackMte2ToMte3Event_[curr]);
if (t + 1 < len) {
const int64_t xOffsetNext = static_cast<int64_t>(start + t + 1) * dim + channelStart;
if (t > 0) {
WaitFlag<HardEvent::MTE3_MTE2>(specWritebackMte3ToMte2Event_[next]);
}
DataCopy(nextBuf, xGm[xOffsetNext], baseDim);
SetFlag<HardEvent::MTE2_MTE3>(specWritebackMte2ToMte3Event_[next]);
}
const int64_t dstOffset =
static_cast<int64_t>(cacheIdx) * stateLen * dim + static_cast<int64_t>(keep + t) * dim + channelStart;
DataCopy(convStatesGm[dstOffset], currBuf, baseDim);
SetFlag<HardEvent::MTE3_MTE2>(specWritebackMte3ToMte2Event_[curr]);
}
WaitFlag<HardEvent::MTE3_MTE2>(specWritebackMte3ToMte2Event_[0]);
if (len > 1) {
WaitFlag<HardEvent::MTE3_MTE2>(specWritebackMte3ToMte2Event_[1]);
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::ResolveSeqTaskWindow(int32_t seq, int32_t inputMode, int32_t seqLen,
int32_t &start, int32_t &len) const
{
switch (GetSeqTaskWindowMode(inputMode)) {
case SEQ_TASK_WINDOW_MODE_VARLEN:
return ResolveSeqTaskWindowByMode<SEQ_TASK_WINDOW_MODE_VARLEN>(seq, seqLen, start, len);
case SEQ_TASK_WINDOW_MODE_DECODE2D:
return ResolveSeqTaskWindowByMode<SEQ_TASK_WINDOW_MODE_DECODE2D>(seq, seqLen, start, len);
default:
return ResolveSeqTaskWindowByMode<SEQ_TASK_WINDOW_MODE_BATCH>(seq, seqLen, start, len);
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
template <int32_t kWindowMode>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::ResolveSeqTaskWindowByMode(int32_t seq, int32_t seqLen, int32_t &start,
int32_t &len) const
{
SeqTaskWindow window;
if constexpr (kWindowMode == SEQ_TASK_WINDOW_MODE_VARLEN) {
const int32_t startVal = ReadQueryStartLocValue(seq);
const int32_t endVal = ReadQueryStartLocValue(seq + 1);
if (startVal < 0 || endVal < startVal || endVal > tilingData_->cuSeqlen) {
return false;
}
window = BuildSeqTaskWindowVarlen(startVal, endVal);
} else if constexpr (kWindowMode == SEQ_TASK_WINDOW_MODE_DECODE2D) {
window = BuildSeqTaskWindowDecode2D(seq);
} else {
window = BuildSeqTaskWindowBatch(seq, seqLen);
}
if (!window.valid) {
return false;
}
start = window.start;
len = window.len;
return true;
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline int32_t CAUSAL_CONV1D_CLASS::ReadQueryStartLocValue(int32_t index) const
{
if (tilingData_->queryStartLocUseInt64 != 0) {
const int64_t value = queryStartLocGmInt64.GetValue(index);
if (value < 0 || value > INT32_MAX_VALUE) {
return -1;
}
return static_cast<int32_t>(value);
}
return queryStartLocGmInt32.GetValue(index);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline int64_t CAUSAL_CONV1D_CLASS::ReadCacheIndexValue(int32_t seq) const
{
const int32_t offset = seq * static_cast<int32_t>(tilingData_->cacheIndicesStride);
if (tilingData_->cacheIndicesUseInt64 != 0) {
return cacheIndicesGmInt64.GetValue(offset);
}
return static_cast<int64_t>(cacheIndicesGmInt32.GetValue(offset));
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::ReadInitialStateModeValue(int32_t seq) const
{
if (tilingData_->initialStateModeDtype == 2) {
return initialStateModeGmInt64.GetValue(seq) != 0;
}
if (tilingData_->initialStateModeDtype == 1) {
return initialStateModeGmInt32.GetValue(seq) != 0;
}
return initialStateModeGmBool.GetValue(seq);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline int32_t CAUSAL_CONV1D_CLASS::ReadNumAcceptedTokensValue(int32_t seq) const
{
if (tilingData_->numAcceptedTokensUseInt64 != 0) {
const int64_t value = numAcceptedTokensGmInt64.GetValue(seq);
if (value <= 0) {
return 0;
}
if (value > INT32_MAX_VALUE) {
return static_cast<int32_t>(INT32_MAX_VALUE);
}
return static_cast<int32_t>(value);
}
return numAcceptedTokensGmInt32.GetValue(seq);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::ResolveSeqCacheIndex(int32_t seq, bool hasCacheIndices,
int32_t &cacheIdx) const
{
cacheIdx = seq;
if (!hasCacheIndices) {
return true;
}
const int64_t cacheIdx64 = ReadCacheIndexValue(seq);
if (cacheIdx64 == tilingData_->padSlotId) {
return false;
}
if (cacheIdx64 < 0 || cacheIdx64 >= tilingData_->numCacheLines) {
return false;
}
cacheIdx = static_cast<int32_t>(cacheIdx64);
return true;
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::ResolveSeqHasInit(int32_t seq, bool hasInitialStateMode) const
{
return hasInitialStateMode ? ReadInitialStateModeValue(seq) : false;
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline void CAUSAL_CONV1D_CLASS::ProcessDefault()
{
switch (GetSeqTaskWindowMode(tilingData_->inputMode)) {
case SEQ_TASK_WINDOW_MODE_VARLEN:
ProcessDefaultByWindowMode<SEQ_TASK_WINDOW_MODE_VARLEN>();
return;
case SEQ_TASK_WINDOW_MODE_DECODE2D:
ProcessDefaultByWindowMode<SEQ_TASK_WINDOW_MODE_DECODE2D>();
return;
default:
ProcessDefaultByWindowMode<SEQ_TASK_WINDOW_MODE_BATCH>();
return;
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
template <int32_t kWindowMode>
__aicore__ inline void CAUSAL_CONV1D_CLASS::ProcessDefaultByWindowMode()
{
const int32_t dim = tilingData_->dim;
const int32_t batch = tilingData_->batch;
const int32_t seqLen = tilingData_->seqLen;
const int32_t baseDim = static_cast<int32_t>(tilingData_->baseDim);
const int32_t baseDimCnt = static_cast<int32_t>(tilingData_->baseDimCnt);
const int32_t width = static_cast<int32_t>(tilingData_->width);
const bool hasCacheIndices = (tilingData_->hasCacheIndices != 0);
const bool hasInit = true;
const bool isSpecDecodingGlobal = IsUpdateSpecDecodingEnabled();
const uint32_t blockIdx = GetBlockIdx();
const uint32_t blockNum = GetBlockNum();
if (baseDim <= 0 || baseDimCnt <= 0 || baseDim > MAX_BLOCK_DIM || width < 2 || width > MAX_WIDTH) {
ReleaseEvents();
return;
}
const int64_t gridSize = static_cast<int64_t>(batch) * baseDimCnt;
for (int64_t task = static_cast<int64_t>(blockIdx); task < gridSize; task += static_cast<int64_t>(blockNum)) {
const int32_t seq = static_cast<int32_t>(task / baseDimCnt);
const int32_t baseDimIdx = static_cast<int32_t>(task % baseDimCnt);
const int32_t channelStart = baseDimIdx * baseDim;
if (channelStart >= dim) {
continue;
}
const int32_t curBaseDim = (channelStart + baseDim <= dim) ? baseDim : (dim - channelStart);
int32_t start = 0;
int32_t len = 0;
if (!ResolveSeqTaskWindowByMode<kWindowMode>(seq, seqLen, start, len)) {
continue;
}
int32_t cacheIdx = 0;
if (!ResolveSeqCacheIndex(seq, hasCacheIndices, cacheIdx)) {
continue;
}
int32_t stateTokenOffset = 0;
if (isSpecDecodingGlobal) {
int32_t accepted = ReadNumAcceptedTokensValue(seq);
stateTokenOffset = accepted - 1;
const int32_t maxOffset = static_cast<int32_t>(tilingData_->stateLen - (width - 1));
if (stateTokenOffset < 0) {
stateTokenOffset = 0;
} else if (stateTokenOffset > maxOffset) {
stateTokenOffset = maxOffset;
}
}
LoadWeightAndBias(channelStart, curBaseDim);
InitRing(cacheIdx, hasInit, stateTokenOffset, start, len, channelStart, curBaseDim, dim);
RunSeq(start, len, channelStart, curBaseDim, dim);
if (isSpecDecodingGlobal) {
DrainTaskMte3();
WriteBackStateSpec(cacheIdx, hasInit, stateTokenOffset, start, len, channelStart, curBaseDim, dim);
} else {
WriteBackState(cacheIdx, len, channelStart, curBaseDim, dim);
}
DrainTaskMte3();
}
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline const CausalConv1dTilingData *CAUSAL_CONV1D_CLASS::GetTilingData() const
{
return tilingData_;
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::HasActivation() const
{
return (tilingData_ != nullptr) && (tilingData_->activationMode != 0);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::HasBias() const
{
return (tilingData_ != nullptr) && (tilingData_->hasBias != 0);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::IsUpdateMode() const
{
return kIsUpdateMode;
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::IsFnRollingFastPathEnabled() const
{
return !kIsUpdateMode && (tilingData_ != nullptr) && (kFnExecutionPlan != FN_EXECUTION_PLAN_INVALID) &&
(tilingData_->hasNumAcceptedTokens == 0) && !HasBias();
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::HasExplicitFnTokenSeqRanges() const
{
return !kIsUpdateMode && (tilingData_ != nullptr) && (tilingData_->inputMode == 0) &&
(tilingData_->hasExplicitTokenSeqRanges != 0) &&
(tilingData_->explicitTokenSeqRangeCount >= tilingData_->tokenBlockCnt);
}
template <CAUSAL_CONV1D_TEMPLATE_ARGS>
__aicore__ inline bool CAUSAL_CONV1D_CLASS::IsUpdateSpecDecodingEnabled() const
{
return kIsUpdateMode && (tilingData_->hasNumAcceptedTokens != 0) && (tilingData_->width == 4);
}
#include "causal_conv1d_fn_tasks.h"
#undef CAUSAL_CONV1D_CLASS
#undef CAUSAL_CONV1D_TEMPLATE_ARGS
} // namespace NsCausalConv1d
#endif // CAUSAL_CONV1D_H