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Unverified Commit cd167e49 authored by Chao Liu's avatar Chao Liu Committed by GitHub
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Compile for gfx908 and gfx90a (#130) 

* adding compilation for multiple targets

* fix build

* clean

* update Jekinsfile

* update readme

* update Jenkins

* use ck::half_t instead of ushort for bf16

* rename enum classes

* clean

* rename

* clean
parent ecf337ba
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Showing with 172 additions and 172 deletions
library/include/ck/library/obselete_driver_offline/driver_gemm_dlops_v1r2.hpp
View file @ cd167e49
......@@ -10,7 +10,7 @@ template <ck::index_t BlockSize,
typename FloatAB,
typename FloatAcc,
typename FloatC,
ck::InMemoryDataOperationEnum_t CGlobalMemoryDataOperation,
ck::InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename AKMGridDesc,
typename BKNGridDesc,
typename CMNGridDesc,
......
library/include/ck/library/obselete_driver_offline/driver_gemm_dlops_v1r3.hpp
View file @ cd167e49
......@@ -10,7 +10,7 @@ template <ck::index_t BlockSize,
typename FloatAB,
typename FloatAcc,
typename FloatC,
ck::InMemoryDataOperationEnum_t CGlobalMemoryDataOperation,
ck::InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename AK0MK1GridDesc,
typename BK0NK1GridDesc,
typename CMNGridDesc,
......
library/include/ck/library/obselete_driver_offline/driver_gemm_xdlops_v2r3.hpp
View file @ cd167e49
......@@ -11,7 +11,7 @@ template <ck::index_t BlockSize,
typename FloatAB,
typename FloatAcc,
typename FloatC,
ck::InMemoryDataOperationEnum_t CGlobalMemoryDataOperation,
ck::InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename AGridDesc_K0_M_K1,
typename BGridDesc_K0_N_K,
typename CMNGridDesc,
......
library/include/ck/library/obselete_driver_offline/driver_gemm_xdlops_v2r4.hpp
View file @ cd167e49
......@@ -10,7 +10,7 @@ template <ck::index_t BlockSize,
typename FloatAB,
typename FloatAcc,
typename FloatC,
ck::InMemoryDataOperationEnum_t CGlobalMemoryDataOperation,
ck::InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename ABK0MK1GridDesc,
typename BBK0NK1GridDesc,
typename CMNGridDesc,
......
library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise.hpp
View file @ cd167e49
......@@ -47,7 +47,7 @@ using reduce_configuration_2_instances_blockwise = std::tuple<
>;
#endif
template <typename AccDataType, ReduceTensorOp_t ReduceOpId>
template <typename AccDataType, ReduceTensorOp ReduceOpId>
using deviceReduceBlockWisePtrType = DeviceReducePtr<
typename reduce_unary_operator<AccDataType, ReduceOpId, true, true>::InElementwiseOperation,
typename reduce_unary_operator<AccDataType, ReduceOpId, true, true>::AccElementwiseOperation>;
......@@ -57,9 +57,9 @@ template <typename InDataType,
typename OutDataType,
int Rank,
int NumReduceDim,
ReduceTensorOp_t ReduceOpId,
NanPropagation_t NanOpt,
ReduceTensorIndices_t IndicesOpt>
ReduceTensorOp ReduceOpId,
NanPropagation NanOpt,
ReduceTensorIndices IndicesOpt>
void add_device_reduce_instance_blockwise(
std::vector<deviceReduceBlockWisePtrType<AccDataType, ReduceOpId>>& device_op_instances)
{
......@@ -71,11 +71,11 @@ void add_device_reduce_instance_blockwise(
AccElementwiseOperation;
constexpr bool Indexable =
(ReduceOpId == ReduceTensorOp_t::MIN || ReduceOpId == ReduceTensorOp_t::MAX ||
ReduceOpId == ReduceTensorOp_t::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices_t::NO_INDICES);
(ReduceOpId == ReduceTensorOp::MIN || ReduceOpId == ReduceTensorOp::MAX ||
ReduceOpId == ReduceTensorOp::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices::NO_INDICES);
constexpr bool PropagateNan = (NanOpt == NanPropagation_t::NOT_PROPAGATE_NAN) ? false : true;
constexpr bool PropagateNan = (NanOpt == NanPropagation::NOT_PROPAGATE_NAN) ? false : true;
static_for<0, std::tuple_size<reduce_configuration_1_instances>::value, 1>{}([&](auto i) {
using cfg1 =
......@@ -128,9 +128,9 @@ void add_device_reduce_instance_blockwise(
ADD_BLOCKWISE_INST_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......@@ -155,9 +155,9 @@ void add_device_reduce_instance_blockwise(
ADD_BLOCKWISE_INST_REF_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......
library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_second_call.hpp
View file @ cd167e49
......@@ -34,7 +34,7 @@ using reduce_configuration_2_instances_blockwise_second_call = std::tuple<
>;
#endif
template <typename AccDataType, ReduceTensorOp_t ReduceOpId>
template <typename AccDataType, ReduceTensorOp ReduceOpId>
using deviceReduceBlockWiseSecondCallPtrType = DeviceReducePtr<
typename reduce_unary_operator<AccDataType, ReduceOpId, false, true>::InElementwiseOperation,
typename reduce_unary_operator<AccDataType, ReduceOpId, false, true>::AccElementwiseOperation>;
......@@ -44,9 +44,9 @@ template <typename InDataType,
typename OutDataType,
int Rank,
int NumReduceDim,
ReduceTensorOp_t ReduceOpId,
NanPropagation_t NanOpt,
ReduceTensorIndices_t IndicesOpt>
ReduceTensorOp ReduceOpId,
NanPropagation NanOpt,
ReduceTensorIndices IndicesOpt>
void add_device_reduce_instance_blockwise_second_call(
std::vector<deviceReduceBlockWiseSecondCallPtrType<AccDataType, ReduceOpId>>&
device_op_instances)
......@@ -60,11 +60,11 @@ void add_device_reduce_instance_blockwise_second_call(
AccElementwiseOperation;
constexpr bool Indexable =
(ReduceOpId == ReduceTensorOp_t::MIN || ReduceOpId == ReduceTensorOp_t::MAX ||
ReduceOpId == ReduceTensorOp_t::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices_t::NO_INDICES);
(ReduceOpId == ReduceTensorOp::MIN || ReduceOpId == ReduceTensorOp::MAX ||
ReduceOpId == ReduceTensorOp::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices::NO_INDICES);
constexpr bool PropagateNan = (NanOpt == NanPropagation_t::NOT_PROPAGATE_NAN) ? false : true;
constexpr bool PropagateNan = (NanOpt == NanPropagation::NOT_PROPAGATE_NAN) ? false : true;
static_assert(std::is_same<InDataType, AccDataType>::value,
"InDataType and AccDataType should be the same to use "
......@@ -122,9 +122,9 @@ void add_device_reduce_instance_blockwise_second_call(
ADD_BLOCKWISE_SECOND_CALL_INST_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......@@ -150,9 +150,9 @@ void add_device_reduce_instance_blockwise_second_call(
ADD_BLOCKWISE_SECOND_CALL_INST_REF_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......
library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_atomic_add.hpp
View file @ cd167e49
......@@ -47,7 +47,7 @@ using reduce_configuration_2_instances_multiblock_atomic_add = std::tuple<
>;
#endif
template <typename AccDataType, ReduceTensorOp_t ReduceOperation>
template <typename AccDataType, ReduceTensorOp ReduceOperation>
using deviceReduceMultiBlockAtomicAddPtrType =
DeviceReducePtr<typename reduce_unary_operator<AccDataType, ReduceOperation, true, true>::
InElementwiseOperation,
......@@ -59,9 +59,9 @@ template <typename InDataType,
typename OutDataType,
int Rank,
int NumReduceDim,
ReduceTensorOp_t ReduceOpId,
NanPropagation_t NanOpt,
ReduceTensorIndices_t IndicesOpt>
ReduceTensorOp ReduceOpId,
NanPropagation NanOpt,
ReduceTensorIndices IndicesOpt>
void add_device_reduce_instance_multiblock_atomic_add(
std::vector<deviceReduceMultiBlockAtomicAddPtrType<AccDataType, ReduceOpId>>&
device_op_instances)
......@@ -74,18 +74,18 @@ void add_device_reduce_instance_multiblock_atomic_add(
AccElementwiseOperation;
constexpr bool Indexable =
(ReduceOpId == ReduceTensorOp_t::MIN || ReduceOpId == ReduceTensorOp_t::MAX ||
ReduceOpId == ReduceTensorOp_t::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices_t::NO_INDICES);
(ReduceOpId == ReduceTensorOp::MIN || ReduceOpId == ReduceTensorOp::MAX ||
ReduceOpId == ReduceTensorOp::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices::NO_INDICES);
constexpr bool PropagateNan = (NanOpt == NanPropagation_t::NOT_PROPAGATE_NAN) ? false : true;
constexpr bool PropagateNan = (NanOpt == NanPropagation::NOT_PROPAGATE_NAN) ? false : true;
static_assert(IndicesOpt == ReduceTensorIndices_t::NO_INDICES,
static_assert(IndicesOpt == ReduceTensorIndices::NO_INDICES,
"AtomicAdd can only be used with reduction operations without indices!");
constexpr bool op_acceptable =
(ReduceOpId == ReduceTensorOp_t::ADD || ReduceOpId == ReduceTensorOp_t::MUL ||
ReduceOpId == ReduceTensorOp_t::AVG || ReduceOpId == ReduceTensorOp_t::NORM1);
(ReduceOpId == ReduceTensorOp::ADD || ReduceOpId == ReduceTensorOp::MUL ||
ReduceOpId == ReduceTensorOp::AVG || ReduceOpId == ReduceTensorOp::NORM1);
constexpr bool out_type_acceptable =
(std::is_same<OutDataType, float>::value || std::is_same<OutDataType, double>::value);
......@@ -149,9 +149,9 @@ void add_device_reduce_instance_multiblock_atomic_add(
ADD_MULTIBLOCK_ATOMIC_ADD_INST_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......@@ -176,9 +176,9 @@ void add_device_reduce_instance_multiblock_atomic_add(
ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......
library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_partial_reduce.hpp
View file @ cd167e49
......@@ -46,7 +46,7 @@ using reduce_configuration_2_instances_multiblock_partial_reduce = std::tuple<
>;
#endif
template <typename AccDataType, ReduceTensorOp_t ReduceOpId>
template <typename AccDataType, ReduceTensorOp ReduceOpId>
using deviceReduceMultiBlockPartialReducePtrType = DeviceReducePtr<
typename reduce_unary_operator<AccDataType, ReduceOpId, true, false>::InElementwiseOperation,
typename reduce_unary_operator<AccDataType, ReduceOpId, true, false>::AccElementwiseOperation>;
......@@ -56,9 +56,9 @@ template <typename InDataType,
typename OutDataType,
int Rank,
int NumReduceDim,
ReduceTensorOp_t ReduceOpId,
NanPropagation_t NanOpt,
ReduceTensorIndices_t IndicesOpt>
ReduceTensorOp ReduceOpId,
NanPropagation NanOpt,
ReduceTensorIndices IndicesOpt>
void add_device_reduce_instance_multiblock_partial_reduce(
std::vector<deviceReduceMultiBlockPartialReducePtrType<AccDataType, ReduceOpId>>&
device_op_instances)
......@@ -72,11 +72,11 @@ void add_device_reduce_instance_multiblock_partial_reduce(
AccElementwiseOperation;
constexpr bool Indexable =
(ReduceOpId == ReduceTensorOp_t::MIN || ReduceOpId == ReduceTensorOp_t::MAX ||
ReduceOpId == ReduceTensorOp_t::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices_t::NO_INDICES);
(ReduceOpId == ReduceTensorOp::MIN || ReduceOpId == ReduceTensorOp::MAX ||
ReduceOpId == ReduceTensorOp::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices::NO_INDICES);
constexpr bool PropagateNan = (NanOpt == NanPropagation_t::NOT_PROPAGATE_NAN) ? false : true;
constexpr bool PropagateNan = (NanOpt == NanPropagation::NOT_PROPAGATE_NAN) ? false : true;
static_for<0, std::tuple_size<reduce_configuration_1_instances>::value, 1>{}([&](auto i) {
using cfg1 =
......@@ -131,9 +131,9 @@ void add_device_reduce_instance_multiblock_partial_reduce(
ADD_MULTIBLOCK_PARTIAL_REDUCE_INST_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......@@ -159,9 +159,9 @@ void add_device_reduce_instance_multiblock_partial_reduce(
ADD_MULTIBLOCK_PARTIAL_REDUCE_INST_REF_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......
library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp
View file @ cd167e49
......@@ -47,7 +47,7 @@ using reduce_configuration_2_instances_threadwise = std::tuple<
>;
#endif
template <typename AccDataType, ReduceTensorOp_t ReduceOpId>
template <typename AccDataType, ReduceTensorOp ReduceOpId>
using deviceReduceThreadWisePtrType = DeviceReducePtr<
typename reduce_unary_operator<AccDataType, ReduceOpId, true, true>::InElementwiseOperation,
typename reduce_unary_operator<AccDataType, ReduceOpId, true, true>::AccElementwiseOperation>;
......@@ -57,9 +57,9 @@ template <typename InDataType,
typename OutDataType,
int Rank,
int NumReduceDim,
ReduceTensorOp_t ReduceOpId,
NanPropagation_t NanOpt,
ReduceTensorIndices_t IndicesOpt>
ReduceTensorOp ReduceOpId,
NanPropagation NanOpt,
ReduceTensorIndices IndicesOpt>
void add_device_reduce_instance_threadwise(
std::vector<deviceReduceThreadWisePtrType<AccDataType, ReduceOpId>>& device_op_instances)
{
......@@ -71,11 +71,11 @@ void add_device_reduce_instance_threadwise(
AccElementwiseOperation;
constexpr bool Indexable =
(ReduceOpId == ReduceTensorOp_t::MIN || ReduceOpId == ReduceTensorOp_t::MAX ||
ReduceOpId == ReduceTensorOp_t::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices_t::NO_INDICES);
(ReduceOpId == ReduceTensorOp::MIN || ReduceOpId == ReduceTensorOp::MAX ||
ReduceOpId == ReduceTensorOp::AMAX);
constexpr bool NeedIndices = Indexable && (IndicesOpt != ReduceTensorIndices::NO_INDICES);
constexpr bool PropagateNan = (NanOpt == NanPropagation_t::NOT_PROPAGATE_NAN) ? false : true;
constexpr bool PropagateNan = (NanOpt == NanPropagation::NOT_PROPAGATE_NAN) ? false : true;
using cfg1 = ReductionConfiguration_1<256, 256, 1>;
......@@ -124,9 +124,9 @@ void add_device_reduce_instance_threadwise(
ADD_THREADWISE_INST_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......@@ -151,9 +151,9 @@ void add_device_reduce_instance_threadwise(
ADD_THREADWISE_INST_REF_BY_TYPE(inT, \
compT, \
outT, \
static_cast<ReduceTensorOp_t>(ReduceOpId), \
static_cast<NanPropagation_t>(NanOpt), \
static_cast<ReduceTensorIndices_t>(IndicesOpt), \
static_cast<ReduceTensorOp>(ReduceOpId), \
static_cast<NanPropagation>(NanOpt), \
static_cast<ReduceTensorIndices>(IndicesOpt), \
Rank, \
NumReduceDim)
......
library/src/obselete_driver_offline/conv_add_fwd_driver_offline_nchwc.cpp
View file @ cd167e49
......@@ -39,7 +39,7 @@ void host_direct_convolution_add_nchwc(const Tensor<TIn>& in,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads&,
const ck::ActivTypeEnum_t activ_type)
const ck::ActivTypeEnum activ_type)
{
using namespace ck;
......@@ -117,7 +117,7 @@ int main(int argc, char* argv[])
exit(1);
}
constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::LeakyRelu;
constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::LeakyRelu;
const ConvForwardAlgo algo = static_cast<ConvForwardAlgo>(std::stoi(argv[1]));
const bool do_verification = std::stoi(argv[2]);
......@@ -167,7 +167,7 @@ int main(int argc, char* argv[])
const bool do_log = std::stoi(argv[4]);
const int nrepeat = std::stoi(argv[5]);
constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::LeakyRelu;
constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::LeakyRelu;
#if 0
constexpr auto N = Number<1>{};
......
library/src/obselete_driver_offline/conv_fwd_driver_offline_nchwc.cpp
View file @ cd167e49
......@@ -37,7 +37,7 @@ void host_direct_convolution_nchwc(const Tensor<TIn>& in,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads&,
const ck::ActivTypeEnum_t activ_type)
const ck::ActivTypeEnum activ_type)
{
using namespace ck;
......@@ -102,7 +102,7 @@ int main(int argc, char* argv[])
exit(1);
}
constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::LeakyRelu;
constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::LeakyRelu;
const ConvForwardAlgo algo = static_cast<ConvForwardAlgo>(std::stoi(argv[1]));
const bool do_verification = std::stoi(argv[2]);
......@@ -149,8 +149,8 @@ int main(int argc, char* argv[])
const bool do_log = std::stoi(argv[4]);
const int nrepeat = std::stoi(argv[5]);
// constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::Sigmoid;
constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::LeakyRelu;
// constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::Sigmoid;
constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::LeakyRelu;
#if 0
constexpr auto N = Number<1>{};
......
library/src/obselete_driver_offline/conv_maxpool_fwd_driver_offline_nchwc.cpp
View file @ cd167e49
......@@ -38,7 +38,7 @@ void host_direct_convolution_maxpool_nchwc(const Tensor<TIn>& in,
const ConvDilations& conv_dilations,
const InLeftPads& in_left_pads,
const InRightPads&,
const ck::ActivTypeEnum_t activ_type)
const ck::ActivTypeEnum activ_type)
{
using namespace ck;
......@@ -126,7 +126,7 @@ int main(int argc, char* argv[])
exit(1);
}
constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::LeakyRelu;
constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::LeakyRelu;
const ConvForwardAlgo algo = static_cast<ConvForwardAlgo>(std::stoi(argv[1]));
const bool do_verification = std::stoi(argv[2]);
......@@ -176,7 +176,7 @@ int main(int argc, char* argv[])
const bool do_log = std::stoi(argv[4]);
const int nrepeat = std::stoi(argv[5]);
constexpr ck::ActivTypeEnum_t activ_type = ActivTypeEnum_t::LeakyRelu;
constexpr ck::ActivTypeEnum activ_type = ActivTypeEnum::LeakyRelu;
#if 1
constexpr auto N = Number<1>{};
......
library/src/tensor_operation_instance/gpu/batched_gemm_reduce/device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gkn_gmn_instance.cpp
View file @ cd167e49
......@@ -23,7 +23,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ReduceSum = ck::tensor_operation::element_wise::ReduceSum;
using ReduceSquareSum = ck::tensor_operation::element_wise::ReduceSquareSum;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization_t::Default;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// c[g, m, n] = a[g, m, k] * b[g, n, k]
// d0[g, m] = reduce0(c[g, m, n])
......
library/src/tensor_operation_instance/gpu/batched_gemm_reduce/device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gnk_gmn_instance.cpp
View file @ cd167e49
......@@ -23,7 +23,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ReduceSum = ck::tensor_operation::element_wise::ReduceSum;
using ReduceSquareSum = ck::tensor_operation::element_wise::ReduceSquareSum;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization_t::Default;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// c[g, m, n] = a[g, m, k] * b[g, n, k]
// d0[g, m] = reduce0(c[g, m, n])
......
library/src/tensor_operation_instance/gpu/batched_gemm_reduce/device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gmk_gkn_gmn_instance.cpp
View file @ cd167e49
......@@ -23,7 +23,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ReduceSum = ck::tensor_operation::element_wise::ReduceSum;
using ReduceSquareSum = ck::tensor_operation::element_wise::ReduceSquareSum;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization_t::Default;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// c[g, m, n] = a[g, m, k] * b[g, n, k]
// d0[g, m] = reduce0(c[g, m, n])
......
library/src/tensor_operation_instance/gpu/batched_gemm_reduce/device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gmk_gnk_gmn_instance.cpp
View file @ cd167e49
......@@ -23,7 +23,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ReduceSum = ck::tensor_operation::element_wise::ReduceSum;
using ReduceSquareSum = ck::tensor_operation::element_wise::ReduceSquareSum;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization_t::Default;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// c[g, m, n] = a[g, m, k] * b[g, n, k]
// d0[g, m] = reduce0(c[g, m, n])
......
library/src/tensor_operation_instance/gpu/conv1d_fwd/device_conv1d_fwd_xdl_nwc_kxc_nwk_bf16_instance.cpp
View file @ cd167e49
......@@ -18,13 +18,13 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto ConvFwd1x1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Pad0;
static constexpr auto ConvFwd1x1S1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Stride1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
using device_conv1d_fwd_xdl_nwc_kxc_nwk_bf16_instances = std::tuple<
......
library/src/tensor_operation_instance/gpu/conv1d_fwd/device_conv1d_fwd_xdl_nwc_kxc_nwk_f16_instance.cpp
View file @ cd167e49
......@@ -18,13 +18,13 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto ConvFwd1x1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Pad0;
static constexpr auto ConvFwd1x1S1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Stride1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
using device_conv1d_fwd_xdl_nwc_kxc_nwk_f16_instances = std::tuple<
......
library/src/tensor_operation_instance/gpu/conv1d_fwd/device_conv1d_fwd_xdl_nwc_kxc_nwk_f32_instance.cpp
View file @ cd167e49
......@@ -17,13 +17,13 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto ConvFwd1x1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Pad0;
static constexpr auto ConvFwd1x1S1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Stride1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Stride1Pad0;
//------------------------------------------------------------------------------
// Conv1D
......
library/src/tensor_operation_instance/gpu/conv1d_fwd/device_conv1d_fwd_xdl_nwc_kxc_nwk_int8_instance.cpp
View file @ cd167e49
......@@ -17,13 +17,13 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
static constexpr auto ConvFwd1x1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Pad0;
static constexpr auto ConvFwd1x1S1P0 =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Filter1x1Stride1Pad0;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
using device_conv1d_fwd_xdl_nwc_kxc_nwk_int8_instances =
......
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