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Commit 439cc869 authored by danyao12's avatar danyao12
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Merge branch 'mha-train-develop' into mha-train-ldsbypass

parents f752739c 4b0a5069
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Showing with 135 additions and 170 deletions
example/32_batched_gemm_scale_softmax_gemm/batched_multihead_attention_forward_v1.cpp
View file @ 439cc869
......@@ -52,8 +52,8 @@ using CShuffleDataType = F32;
using CDataType = DataType;
using ZDataType = U16; // INT32
using LSEDataType = F32;
using Acc0BiasDataType = ck::Tuple<>;
using Acc1BiasDataType = ck::Tuple<>;
using Acc0BiasDataType = void;
using Acc1BiasDataType = void;
static constexpr ck::index_t NumDimG = 2;
static constexpr ck::index_t NumDimM = 1;
......
example/32_batched_gemm_scale_softmax_gemm/batched_multihead_attention_train_v1.cpp
View file @ 439cc869
......@@ -125,8 +125,8 @@ using DeviceGemmInstanceFWD =
GemmDataType,
ZDataType,
LSEDataType,
Acc0BiasDataType,
Acc1BiasDataType,
void,
void,
AccDataType,
ShuffleDataType,
QKVElementOp,
......@@ -259,8 +259,8 @@ using DeviceGemmInstanceFWD =
GemmDataType,
ZDataType,
LSEDataType,
Acc0BiasDataType,
Acc1BiasDataType,
void,
void,
AccDataType,
ShuffleDataType,
QKVElementOp,
......@@ -463,8 +463,8 @@ using DeviceGemmInstanceFWD =
GemmDataType,
ZDataType,
LSEDataType,
Acc0BiasDataType,
Acc1BiasDataType,
void,
void,
AccDataType,
ShuffleDataType,
QKVElementOp,
......
example/32_batched_gemm_scale_softmax_gemm/batched_multihead_attention_train_v2.cpp
View file @ 439cc869
......@@ -79,8 +79,8 @@ using AccDataType = F32;
using ShuffleDataType = F32;
using LSEDataType = F32;
using ZDataType = U16; // INT32
using Acc0BiasDataType = void;
using Acc1BiasDataType = void;
using Acc0BiasDataType = ck::Tuple<>;
using Acc1BiasDataType = ck::Tuple<>;
static constexpr ck::index_t NumDimG = 2;
static constexpr ck::index_t NumDimM = 1;
......@@ -117,7 +117,7 @@ using DeviceGemmInstanceFWD =
// #################################################################################| | | | | | | | | | | | | | | DataType| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| | | | | Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| Step| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcScalar| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| _NPerBlock| SrcScalar| | |
// #################################################################################| | | | | | | | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | | | | | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerVector| Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| | PerVector| | |
// #################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
ck::tensor_operation::device::DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, Acc0BiasDataType, Acc1BiasDataType, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 32, 32, 8, 8, 2, 32, 32, 1, 4, 1, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 4, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 2, false, 1, 1, S<1, 64, 1, 4>, 8, 4, MaskingSpec, Deterministic>;
ck::tensor_operation::device::DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, void, void, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 32, 32, 8, 8, 2, 32, 32, 1, 4, 1, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 4, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 2, false, 1, 1, S<1, 64, 1, 4>, 8, 4, MaskingSpec, Deterministic>;
using DeviceGemmInstanceBWD =
// ########################################################################################| NumDimG| NumDimM| NumDimN| NumDimK| NumDimO| InputDataType| OutputDataType| GemmDataType| ZDataType| LSEDataType| Acc0BiasDataType| Acc1BiasDataType| GemmAcc| CShuffle| A| B| Acc| B1| C| GEMM| ATensorSpec| B0TensorSpec| B1TensorSpec| CTensorSpec| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| Gemm2| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CShuffleBlockTransferScalarPerVector_NPerBlock| MaskingSpec| Deterministic|
......@@ -133,7 +133,7 @@ using DeviceGemmInstanceFWD =
// #################################################################################| | | | | | | | | | | | | | | DataType| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| | | | | Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| Step| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcScalar| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| _NPerBlock| SrcScalar| | |
// #################################################################################| | | | | | | | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | | | | | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerVector| Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| | PerVector| | |
// #################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
ck::tensor_operation::device::DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, Acc0BiasDataType, Acc1BiasDataType, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 4, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 4, MaskingSpec, Deterministic>;
ck::tensor_operation::device::DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, void, void, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 4, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 4, MaskingSpec, Deterministic>;
using DeviceGemmInstanceBWD =
// ########################################################################################| NumDimG| NumDimM| NumDimN| NumDimK| NumDimO| InputDataType| OutputDataType| GemmDataType| ZDataType| LSEDataType| Acc0BiasDataType| Acc1BiasDataType| GemmAcc| CShuffle| A| B| Acc| B1| C| GEMM| ATensorSpec| B0TensorSpec| B1TensorSpec| CTensorSpec| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| Gemm2| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CShuffleBlockTransferScalarPerVector_NPerBlock| MaskingSpec| Deterministic|
......@@ -156,7 +156,7 @@ using DeviceGemmInstanceFWD =
// #################################################################################| | | | | | | | | | | | | | | DataType| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| | | | | Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| Step| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcScalar| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| _NPerBlock| SrcScalar| | |
// #################################################################################| | | | | | | | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | | | | | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerVector| Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| | PerVector| | |
// #################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
ck::tensor_operation::device::DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, Acc0BiasDataType, Acc1BiasDataType, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 4, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 4, MaskingSpec, Deterministic>;
ck::tensor_operation::device::DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, void, void, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 4, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 4, MaskingSpec, Deterministic>;
using DeviceGemmInstanceBWD =
// ########################################################################################| NumDimG| NumDimM| NumDimN| NumDimK| NumDimO| InputDataType| OutputDataType| GemmDataType| ZDataType| LSEDataType| Acc0BiasDataType| Acc1BiasDataType| GemmAcc| CShuffle| A| B| Acc| B1| C| GEMM| ATensorSpec| B0TensorSpec| B1TensorSpec| CTensorSpec| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| Gemm2| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CShuffleBlockTransferScalarPerVector_NPerBlock| MaskingSpec| Deterministic|
......@@ -594,8 +594,8 @@ int run(int argc, char* argv[])
static_cast<OutputDataType*>(qgrad_device_buf.GetDeviceBuffer()),
static_cast<OutputDataType*>(kgrad_device_buf.GetDeviceBuffer()),
static_cast<OutputDataType*>(vgrad_device_buf.GetDeviceBuffer()),
nullptr, // p_acc0_biases;
nullptr, // p_acc1_biases;
{}, // p_acc0_biases;
{}, // p_acc1_biases;
q_gs_ms_ks_lengths,
q_gs_ms_ks_strides,
k_gs_ns_ks_lengths,
......
example/32_batched_gemm_scale_softmax_gemm/grouped_multihead_attention_forward_v1.cpp
View file @ 439cc869
......@@ -52,8 +52,8 @@ using CShuffleDataType = F32;
using CDataType = DataType;
using ZDataType = U16; // INT32
using LSEDataType = F32;
using Acc0BiasDataType = ck::Tuple<>;
using Acc1BiasDataType = ck::Tuple<>;
using Acc0BiasDataType = void;
using Acc1BiasDataType = void;
static constexpr ck::index_t NumDimG = 2;
static constexpr ck::index_t NumDimM = 1;
......
example/32_batched_gemm_scale_softmax_gemm/grouped_multihead_attention_train_v1.cpp
View file @ 439cc869
......@@ -124,8 +124,8 @@ using DeviceGemmInstanceFWD =
GemmDataType,
ZDataType,
LSEDataType,
Acc0BiasDataType,
Acc1BiasDataType,
void,
void,
AccDataType,
ShuffleDataType,
QKVElementOp,
......@@ -258,8 +258,8 @@ using DeviceGemmInstanceFWD =
GemmDataType,
ZDataType,
LSEDataType,
Acc0BiasDataType,
Acc1BiasDataType,
void,
void,
AccDataType,
ShuffleDataType,
QKVElementOp,
......@@ -462,8 +462,8 @@ using DeviceGemmInstanceFWD =
GemmDataType,
ZDataType,
LSEDataType,
Acc0BiasDataType,
Acc1BiasDataType,
void,
void,
AccDataType,
ShuffleDataType,
QKVElementOp,
......
example/32_batched_gemm_scale_softmax_gemm/grouped_multihead_attention_train_v2.cpp
View file @ 439cc869
......@@ -78,8 +78,8 @@ using AccDataType = F32;
using ShuffleDataType = F32;
using LSEDataType = F32;
using ZDataType = U16; // INT32
using Acc0BiasDataType = void;
using Acc1BiasDataType = void;
using Acc0BiasDataType = ck::Tuple<>;
using Acc1BiasDataType = ck::Tuple<>;
static constexpr ck::index_t NumDimG = 2;
static constexpr ck::index_t NumDimM = 1;
......@@ -116,7 +116,7 @@ using DeviceGemmInstanceFWD =
// #################################################################################| | | | | | | | | | | | | | | DataType| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| | | | | Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| Step| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcScalar| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| _NPerBlock| SrcScalar| | |
// #################################################################################| | | | | | | | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | | | | | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerVector| Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| | PerVector| | |
// #################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
ck::tensor_operation::device::DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, Acc0BiasDataType, Acc1BiasDataType, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 32, 32, 8, 8, 2, 32, 32, 1, 4, 1, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 2, false, 1, 1, S<1, 64, 1, 4>, 8, 1, MaskingSpec, Deterministic>;
ck::tensor_operation::device::DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, void, void, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 32, 32, 8, 8, 2, 32, 32, 1, 4, 1, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 2, false, 1, 1, S<1, 64, 1, 4>, 8, 1, MaskingSpec, Deterministic>;
using DeviceGemmInstanceBWD =
// ########################################################################################| NumDimG| NumDimM| NumDimN| NumDimK| NumDimO| InputDataType| OutputDataType| GemmDataType| ZDataType| LSEDataType| Acc0BiasDataType| Acc1BiasDataType| GemmAcc| CShuffle| A| B| Acc| B1| C| GEMM| ATensorSpec| B0TensorSpec| B1TensorSpec| CTensorSpec| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| Gemm2| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CShuffleBlockTransferScalarPerVector_NPerBlock| MaskingSpec| Deterministic|
......@@ -132,7 +132,7 @@ using DeviceGemmInstanceFWD =
// #################################################################################| | | | | | | | | | | | | | | DataType| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| | | | | Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| Step| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcScalar| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| _NPerBlock| SrcScalar| | |
// #################################################################################| | | | | | | | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | | | | | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerVector| Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| | PerVector| | |
// #################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
ck::tensor_operation::device::DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, Acc0BiasDataType, Acc1BiasDataType, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 1, MaskingSpec, Deterministic>;
ck::tensor_operation::device::DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, void, void, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 1, MaskingSpec, Deterministic>;
using DeviceGemmInstanceBWD =
// ########################################################################################| NumDimG| NumDimM| NumDimN| NumDimK| NumDimO| InputDataType| OutputDataType| GemmDataType| ZDataType| LSEDataType| Acc0BiasDataType| Acc1BiasDataType| GemmAcc| CShuffle| A| B| Acc| B1| C| GEMM| ATensorSpec| B0TensorSpec| B1TensorSpec| CTensorSpec| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| Gemm2| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CShuffleBlockTransferScalarPerVector_NPerBlock| MaskingSpec| Deterministic|
......@@ -155,7 +155,7 @@ using DeviceGemmInstanceFWD =
// #################################################################################| | | | | | | | | | | | | | | DataType| DataType| Elementwise| Elementwise| Elementwise| Elementwise| Elementwise| Specialization| | | | | Prefetch| Size| MPer| NPer| KPer| NPer| KPer| | | | XDL| XDL| MXdl| NXdl| NXdl| Step| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcScalar| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| _NPerBlock| SrcScalar| | |
// #################################################################################| | | | | | | | | | | | | | | | | Operation| Operation| Operation| Operation| Operation| | | | | | Stage| | Block| Block| Block| Block| Block| | | | | | Per| Per| Per| | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerVector| Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| | PerVector| | |
// #################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Wave| Wave| Wave| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
ck::tensor_operation::device::DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, Acc0BiasDataType, Acc1BiasDataType, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 1, MaskingSpec, Deterministic>;
ck::tensor_operation::device::DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V2< NumDimG, NumDimM, NumDimN, NumDimK, NumDimO, InputDataType, InputDataType, InputDataType, InputDataType, GemmDataType, ZDataType, LSEDataType, void, void, AccDataType, ShuffleDataType, QKVElementOp, QKVElementOp, Scale, QKVElementOp, YElementOp, GemmSpec, TensorSpecQ, TensorSpecK, TensorSpecV, TensorSpecY, 1, 256, 128, 128, 32, 64, 32, 8, 8, 2, 32, 32, 1, 4, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, S<16, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 2, S<1, 32, 1, 8>, 8, 1, MaskingSpec, Deterministic>;
using DeviceGemmInstanceBWD =
// ########################################################################################| NumDimG| NumDimM| NumDimN| NumDimK| NumDimO| InputDataType| OutputDataType| GemmDataType| ZDataType| LSEDataType| Acc0BiasDataType| Acc1BiasDataType| GemmAcc| CShuffle| A| B| Acc| B1| C| GEMM| ATensorSpec| B0TensorSpec| B1TensorSpec| CTensorSpec| NumGemmK| Block| Gemm01| Gemm0| Gemm0| Gemm1| Gemm1| AK1| BK1| B1K1| MPer| NPer| Gemm0| Gemm0| Gemm1| Gemm2| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockTransfer| B0BlockLds| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockTransfer| B1BlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CShuffleBlockTransferScalarPerVector_NPerBlock| MaskingSpec| Deterministic|
......
include/ck/tensor_operation/gpu/device/device_batched_gemm_softmax_gemm_permute.hpp
View file @ 439cc869
......@@ -94,8 +94,8 @@ struct DeviceBatchedMultiheadAttentionForward : public BaseOperator
void* p_c,
void* p_z,
void* p_lse,
const void* p_acc0_biases,
const void* p_acc1_biases,
const void* p_acc0_bias,
const void* p_acc1_bias,
const std::vector<index_t>& a_gs_ms_ks_lengths,
const std::vector<index_t>& a_gs_ms_ks_strides,
const std::vector<index_t>& b_gs_ns_ks_lengths,
......@@ -107,12 +107,10 @@ struct DeviceBatchedMultiheadAttentionForward : public BaseOperator
const std::vector<index_t>& z_gs_ms_ns_lengths, // z_gs_ms_os_lengths
const std::vector<index_t>& z_gs_ms_ns_strides, // z_gs_ms_os_strides
const std::vector<index_t>& lse_gs_ms_lengths, // lse_gs_ms_lengths
const std::vector<index_t>& acc0_biases_gs_ms_ns_lengths,
const std::vector<index_t>& acc0_biases_gs_ms_ns_strides,
const std::vector<index_t>&
acc1_biases_gs_ms_gemm1ns_lengths, // acc1_biases_gs_ms_os_lengths
const std::vector<index_t>&
acc1_biases_gs_ms_gemm1ns_strides, // acc1_biases_gs_ms_os_strides
const std::vector<index_t>& acc0_bias_gs_ms_ns_lengths,
const std::vector<index_t>& acc0_bias_gs_ms_ns_strides,
const std::vector<index_t>& acc1_bias_gs_ms_gemm1ns_lengths,
const std::vector<index_t>& acc1_bias_gs_ms_gemm1ns_strides,
AElementwiseOperation a_element_op,
B0ElementwiseOperation b0_element_op,
Acc0ElementwiseOperation acc0_element_op,
......
include/ck/tensor_operation/gpu/device/device_grouped_gemm_softmax_gemm_permute.hpp
View file @ 439cc869
......@@ -125,8 +125,8 @@ struct DeviceGroupedMultiheadAttentionForward : public BaseOperator
std::vector<void*> p_c_vec,
std::vector<void*> p_z_vec,
std::vector<void*> p_lse_vec,
std::vector<const void*> p_acc0_biases_vec,
std::vector<const void*> p_acc1_biases_vec,
std::vector<const void*> p_acc0_bias_vec,
std::vector<const void*> p_acc1_bias_vec,
std::vector<ProblemDesc>& problem_desc_vec,
AElementwiseOperation a_element_op,
B0ElementwiseOperation b0_element_op,
......
include/ck/tensor_operation/gpu/device/impl/device_batched_mha_fwd_xdl_cshuffle_v1.hpp
View file @ 439cc869
......@@ -289,12 +289,6 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
static_assert(NumDimG > 0 && NumDimM > 0 && NumDimN > 0 && NumDimK > 0 && NumDimO > 0,
"Number of dimension must be greater than 0");
static constexpr index_t NumAcc0Bias = Acc0BiasDataType::Size();
static constexpr index_t NumAcc1Bias = Acc1BiasDataType::Size();
// TODO ANT: implement bias combination
static_assert(NumAcc0Bias == 0 && NumAcc0Bias == 0, "Bias addition is unimplemented");
#if 0
// TODO ANT: use alias
static constexpr index_t NumDimGemm0M = NumDimM;
......@@ -535,39 +529,36 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
// FIXME: constness
struct Argument : public BaseArgument
{
Argument(
const ADataType* p_a_grid,
const BDataType* p_b_grid,
const B1DataType* p_b1_grid,
CDataType* p_c_grid,
ZDataType* p_z_grid,
LSEDataType* p_lse_grid,
const std::array<void*, NumAcc0Bias> p_acc0_biases,
const std::array<void*, NumAcc1Bias> p_acc1_biases,
const std::vector<index_t>& a_gs_ms_ks_lengths,
const std::vector<index_t>& a_gs_ms_ks_strides,
const std::vector<index_t>& b_gs_ns_ks_lengths,
const std::vector<index_t>& b_gs_ns_ks_strides,
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_lengths, // b1_gs_os_ns_lengths
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_strides, // b1_gs_os_ns_strides
const std::vector<index_t>& c_gs_ms_gemm1ns_lengths, // c_gs_ms_os_lengths
const std::vector<index_t>& c_gs_ms_gemm1ns_strides, // c_gs_ms_os_strides
const std::vector<index_t>& z_gs_ms_ns_lengths,
const std::vector<index_t>& z_gs_ms_ns_strides,
const std::vector<index_t>& lse_gs_ms_lengths,
const std::array<std::vector<ck::index_t>, NumAcc0Bias> acc0_biases_gs_ms_ns_lengths,
const std::array<std::vector<ck::index_t>, NumAcc0Bias> acc0_biases_gs_ms_ns_strides,
const std::array<std::vector<ck::index_t>, NumAcc1Bias>
acc1_biases_gs_ms_gemm1ns_lengths, // acc1_biases_gs_ms_os_lengths
const std::array<std::vector<ck::index_t>, NumAcc1Bias>
acc1_biases_gs_ms_gemm1ns_strides, // acc1_biases_gs_ms_os_strides
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
AccElementwiseOperation acc_element_op,
B1ElementwiseOperation b1_element_op,
CElementwiseOperation c_element_op,
float p_dropout,
std::tuple<unsigned long long, unsigned long long> seeds)
Argument(const ADataType* p_a_grid,
const BDataType* p_b_grid,
const B1DataType* p_b1_grid,
CDataType* p_c_grid,
ZDataType* p_z_grid,
LSEDataType* p_lse_grid,
const void* p_acc0_bias,
const void* p_acc1_bias,
const std::vector<index_t>& a_gs_ms_ks_lengths,
const std::vector<index_t>& a_gs_ms_ks_strides,
const std::vector<index_t>& b_gs_ns_ks_lengths,
const std::vector<index_t>& b_gs_ns_ks_strides,
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_lengths, // b1_gs_os_ns_lengths
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_strides, // b1_gs_os_ns_strides
const std::vector<index_t>& c_gs_ms_gemm1ns_lengths, // c_gs_ms_os_lengths
const std::vector<index_t>& c_gs_ms_gemm1ns_strides, // c_gs_ms_os_strides
const std::vector<index_t>& z_gs_ms_ns_lengths,
const std::vector<index_t>& z_gs_ms_ns_strides,
const std::vector<index_t>& lse_gs_ms_lengths,
const std::vector<ck::index_t> acc0_bias_gs_ms_ns_lengths,
const std::vector<ck::index_t> acc0_bias_gs_ms_ns_strides,
const std::vector<ck::index_t> acc1_bias_gs_ms_gemm1ns_lengths,
const std::vector<ck::index_t> acc1_bias_gs_ms_gemm1ns_strides,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
AccElementwiseOperation acc_element_op,
B1ElementwiseOperation b1_element_op,
CElementwiseOperation c_element_op,
float p_dropout,
std::tuple<unsigned long long, unsigned long long> seeds)
: p_a_grid_{p_a_grid},
p_b_grid_{p_b_grid},
p_b1_grid_{p_b1_grid},
......@@ -624,12 +615,12 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
type_convert<index_t>(lse_grid_desc_m_.GetElementSpaceSize())}
{
// TODO ANT: implement bias addition
ignore = p_acc0_biases;
ignore = p_acc1_biases;
ignore = acc0_biases_gs_ms_ns_lengths;
ignore = acc0_biases_gs_ms_ns_strides;
ignore = acc1_biases_gs_ms_gemm1ns_lengths;
ignore = acc1_biases_gs_ms_gemm1ns_strides;
ignore = p_acc0_bias;
ignore = p_acc1_bias;
ignore = acc0_bias_gs_ms_ns_lengths;
ignore = acc0_bias_gs_ms_ns_strides;
ignore = acc1_bias_gs_ms_gemm1ns_lengths;
ignore = acc1_bias_gs_ms_gemm1ns_strides;
if(GridwiseGemm::CheckValidity(a_grid_desc_ak0_m_ak1_,
b_grid_desc_bk0_n_bk1_,
......@@ -984,39 +975,37 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
}
static auto MakeArgument(
const ADataType* p_a,
const BDataType* p_b,
const B1DataType* p_b1,
CDataType* p_c,
ZDataType* p_z,
LSEDataType* p_lse,
const std::array<void*, NumAcc0Bias> p_acc0_biases,
const std::array<void*, NumAcc1Bias> p_acc1_biases,
const std::vector<index_t>& a_gs_ms_ks_lengths,
const std::vector<index_t>& a_gs_ms_ks_strides,
const std::vector<index_t>& b_gs_ns_ks_lengths,
const std::vector<index_t>& b_gs_ns_ks_strides,
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_lengths, // b1_gs_os_ns_lengths
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_strides, // b1_gs_os_ns_strides
const std::vector<index_t>& c_gs_ms_gemm1ns_lengths, // c_gs_ms_os_lengths
const std::vector<index_t>& c_gs_ms_gemm1ns_strides, // c_gs_ms_os_strides
const std::vector<index_t>& z_gs_ms_ns_lengths,
const std::vector<index_t>& z_gs_ms_ns_strides,
const std::vector<index_t>& lse_gs_ms_lengths,
const std::array<std::vector<ck::index_t>, NumAcc0Bias> acc0_biases_gs_ms_ns_lengths,
const std::array<std::vector<ck::index_t>, NumAcc0Bias> acc0_biases_gs_ms_ns_strides,
const std::array<std::vector<ck::index_t>, NumAcc1Bias>
acc1_biases_gs_ms_gemm1ns_lengths, // acc1_biases_gs_ms_os_lengths
const std::array<std::vector<ck::index_t>, NumAcc1Bias>
acc1_biases_gs_ms_gemm1ns_strides, // acc1_biases_gs_ms_os_strides
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
AccElementwiseOperation acc_element_op,
B1ElementwiseOperation b1_element_op,
CElementwiseOperation c_element_op,
float p_dropout,
std::tuple<unsigned long long, unsigned long long> seeds)
static auto
MakeArgument(const ADataType* p_a,
const BDataType* p_b,
const B1DataType* p_b1,
CDataType* p_c,
ZDataType* p_z,
LSEDataType* p_lse,
const void* p_acc0_bias,
const void* p_acc1_bias,
const std::vector<index_t>& a_gs_ms_ks_lengths,
const std::vector<index_t>& a_gs_ms_ks_strides,
const std::vector<index_t>& b_gs_ns_ks_lengths,
const std::vector<index_t>& b_gs_ns_ks_strides,
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_lengths, // b1_gs_os_ns_lengths
const std::vector<index_t>& b1_gs_gemm1ns_gemm1ks_strides, // b1_gs_os_ns_strides
const std::vector<index_t>& c_gs_ms_gemm1ns_lengths, // c_gs_ms_os_lengths
const std::vector<index_t>& c_gs_ms_gemm1ns_strides, // c_gs_ms_os_strides
const std::vector<index_t>& z_gs_ms_ns_lengths,
const std::vector<index_t>& z_gs_ms_ns_strides,
const std::vector<index_t>& lse_gs_ms_lengths,
const std::vector<ck::index_t>& acc0_bias_gs_ms_ns_lengths,
const std::vector<ck::index_t>& acc0_bias_gs_ms_ns_strides,
const std::vector<ck::index_t>& acc1_bias_gs_ms_gemm1ns_lengths,
const std::vector<ck::index_t>& acc1_bias_gs_ms_gemm1ns_strides,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
AccElementwiseOperation acc_element_op,
B1ElementwiseOperation b1_element_op,
CElementwiseOperation c_element_op,
float p_dropout,
std::tuple<unsigned long long, unsigned long long> seeds)
{
return Argument{p_a,
p_b,
......@@ -1024,8 +1013,8 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
p_c,
p_z,
p_lse,
p_acc0_biases,
p_acc1_biases,
p_acc0_bias,
p_acc1_bias,
a_gs_ms_ks_lengths,
a_gs_ms_ks_strides,
b_gs_ns_ks_lengths,
......@@ -1037,10 +1026,10 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
z_gs_ms_ns_lengths,
z_gs_ms_ns_strides,
lse_gs_ms_lengths,
acc0_biases_gs_ms_ns_lengths,
acc0_biases_gs_ms_ns_strides,
acc1_biases_gs_ms_gemm1ns_lengths, // acc1_biases_gs_ms_os_lengths
acc1_biases_gs_ms_gemm1ns_strides, // acc1_biases_gs_ms_os_strides
acc0_bias_gs_ms_ns_lengths,
acc0_bias_gs_ms_ns_strides,
acc1_bias_gs_ms_gemm1ns_lengths, // acc1_biases_gs_ms_os_lengths
acc1_bias_gs_ms_gemm1ns_strides, // acc1_biases_gs_ms_os_strides
a_element_op,
b_element_op,
acc_element_op,
......@@ -1061,8 +1050,8 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
void* p_c,
void* p_z,
void* p_lse,
const std::array<void*, NumAcc0Bias> p_acc0_biases,
const std::array<void*, NumAcc1Bias> p_acc1_biases,
const void* p_acc0_bias,
const void* p_acc1_bias,
const std::vector<index_t>& a_gs_ms_ks_lengths,
const std::vector<index_t>& a_gs_ms_ks_strides,
const std::vector<index_t>& b_gs_ns_ks_lengths,
......@@ -1074,12 +1063,10 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
const std::vector<index_t>& z_gs_ms_ns_lengths,
const std::vector<index_t>& z_gs_ms_ns_strides,
const std::vector<index_t>& lse_gs_ms_lengths,
const std::array<std::vector<ck::index_t>, NumAcc0Bias> acc0_biases_gs_ms_ns_lengths,
const std::array<std::vector<ck::index_t>, NumAcc0Bias> acc0_biases_gs_ms_ns_strides,
const std::array<std::vector<ck::index_t>, NumAcc1Bias>
acc1_biases_gs_ms_gemm1ns_lengths, // acc1_biases_gs_ms_os_lengths
const std::array<std::vector<ck::index_t>, NumAcc1Bias>
acc1_biases_gs_ms_gemm1ns_strides, // acc1_biases_gs_ms_os_strides
const std::vector<ck::index_t>& acc0_bias_gs_ms_ns_lengths,
const std::vector<ck::index_t>& acc0_bias_gs_ms_ns_strides,
const std::vector<ck::index_t>& acc1_bias_gs_ms_gemm1ns_lengths,
const std::vector<ck::index_t>& acc1_bias_gs_ms_gemm1ns_strides,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
AccElementwiseOperation acc_element_op,
......@@ -1094,8 +1081,8 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
static_cast<CDataType*>(p_c),
static_cast<ZDataType*>(p_z),
static_cast<LSEDataType*>(p_lse),
p_acc0_biases, // cast in struct Argument
p_acc1_biases, // cast in struct Argument
p_acc0_bias, // cast in struct Argument
p_acc1_bias, // cast in struct Argument
a_gs_ms_ks_lengths,
a_gs_ms_ks_strides,
b_gs_ns_ks_lengths,
......@@ -1107,10 +1094,10 @@ struct DeviceBatchedMultiheadAttentionForward_Xdl_CShuffle_V1
z_gs_ms_ns_lengths,
z_gs_ms_ns_strides,
lse_gs_ms_lengths,
acc0_biases_gs_ms_ns_lengths,
acc0_biases_gs_ms_ns_strides,
acc1_biases_gs_ms_gemm1ns_lengths,
acc1_biases_gs_ms_gemm1ns_strides,
acc0_bias_gs_ms_ns_lengths,
acc0_bias_gs_ms_ns_strides,
acc1_bias_gs_ms_gemm1ns_lengths,
acc1_bias_gs_ms_gemm1ns_strides,
a_element_op,
b_element_op,
acc_element_op,
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_mha_fwd_xdl_cshuffle_v1.hpp
View file @ 439cc869
......@@ -279,12 +279,6 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
static_assert(NumDimG > 0 && NumDimM > 0 && NumDimN > 0 && NumDimK > 0 && NumDimO > 0,
"Number of dimension must be greater than 0");
static constexpr index_t NumAcc0Bias = Acc0BiasDataType::Size();
static constexpr index_t NumAcc1Bias = Acc1BiasDataType::Size();
// TODO ANT: implement bias combination
static_assert(NumAcc0Bias == 0 && NumAcc0Bias == 0, "Bias addition is unimplemented");
#if 0
// TODO ANT: use alias
static constexpr index_t NumDimGemm0M = NumDimM;
......@@ -603,8 +597,8 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
std::vector<void*> p_c_vec,
std::vector<void*> p_z_vec,
std::vector<void*> p_lse_vec,
std::vector<std::vector<const void*>> p_acc0_biases_vec,
std::vector<std::vector<const void*>> p_acc1_biases_vec,
std::vector<const void*> p_acc0_bias_vec,
std::vector<const void*> p_acc1_bias_vec,
std::vector<ProblemDesc> problem_desc_vec,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
......@@ -619,6 +613,9 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
b1_element_op_{b1_element_op},
c_element_op_{c_element_op}
{
ignore = p_acc0_bias_vec;
ignore = p_acc1_bias_vec;
// TODO ANT: implement bias addition
group_count_ = problem_desc_vec.size();
......@@ -628,11 +625,6 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
throw std::runtime_error("wrong! group_count_ != a/b/b1/c_vec.size");
}
if(!(p_acc0_biases_vec.size() == p_acc1_biases_vec.size()))
{
throw std::runtime_error("wrong! acc0_bias_vec.size != acc1_bias_vec.size");
}
grid_size_ = 0;
for(std::size_t i = 0; i < group_count_; i++)
......@@ -710,18 +702,6 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
grid_size_ += grid_size_grp;
// for each group, make sure acc0_biases_gs_ms_ns_lengths.size() == NumAcc0Bias and
// so on
if(!(problem_desc.acc0_biases_gs_ms_ns_lengths.size() == NumAcc0Bias &&
problem_desc.acc0_biases_gs_ms_ns_strides.size() == NumAcc0Bias &&
problem_desc.acc1_biases_gs_ms_os_lengths.size() == NumAcc1Bias &&
problem_desc.acc1_biases_gs_ms_os_strides.size() == NumAcc1Bias))
{
throw std::runtime_error(
"wrong! number of biases in function argument does not "
"match that in template argument");
}
group_kernel_args_.push_back({p_a_grid,
p_b_grid,
p_b1_grid,
......@@ -1055,8 +1035,8 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
std::vector<void*> p_c_vec,
std::vector<void*> p_z_vec,
std::vector<void*> p_lse_vec,
std::vector<std::vector<const void*>> p_acc0_biases_vec,
std::vector<std::vector<const void*>> p_acc1_biases_vec,
std::vector<const void*> p_acc0_bias_vec,
std::vector<const void*> p_acc1_bias_vec,
std::vector<ProblemDesc> problem_desc_vec,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
......@@ -1072,8 +1052,8 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
p_c_vec,
p_z_vec,
p_lse_vec,
p_acc0_biases_vec,
p_acc1_biases_vec,
p_acc0_bias_vec,
p_acc1_bias_vec,
problem_desc_vec,
a_element_op,
b_element_op,
......@@ -1094,9 +1074,9 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
std::vector<void*> p_c_vec,
std::vector<void*> p_z_vec,
std::vector<void*> p_lse_vec,
std::vector<std::vector<const void*>> p_acc0_biases_vec,
std::vector<std::vector<const void*>> p_acc1_biases_vec,
std::vector<ProblemDesc> problem_desc_vec,
std::vector<const void*> p_acc0_bias_vec,
std::vector<const void*> p_acc1_bias_vec,
std::vector<ProblemDesc>& problem_desc_vec,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
AccElementwiseOperation acc_element_op,
......@@ -1111,8 +1091,8 @@ struct DeviceGroupedMultiheadAttentionForward_Xdl_CShuffle_V1
p_c_vec,
p_z_vec,
p_lse_vec,
p_acc0_biases_vec,
p_acc1_biases_vec,
p_acc0_bias_vec,
p_acc1_bias_vec,
problem_desc_vec,
a_element_op,
b_element_op,
......
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