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Use double for all scaling values and float-point constant values at the Device Op API (#557)

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* Use double as alpha/beta values type in reduce device op api

* Use double as alpha/beta values type in softmax device op api

* Use double as alpha/beta values type in multiple-reduce device op api

* Use double as epsilon value type in normalization/elementwise-normalization device op api

[ROCm/composable_kernel commit: 52abc2f371]
This commit is contained in:
Qianfeng
2023-01-19 02:02:50 +08:00
committed by GitHub
parent 21a146fb2f
commit fc8fa0992f
24 changed files with 112 additions and 109 deletions
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14
client_example/06_softmax/softmax4d.cpp
View File

@@ -47,8 +47,8 @@ int main(int argc, char* argv[])
ck::index_t num_elements =
std::accumulate(in_lengths.begin(), in_lengths.end(), 1, std::multiplies<ck::index_t>());
AccDataType alpha{2.0f};
AccDataType beta{2.0f};
double alpha{2.0};
double beta{2.0};
SimpleDeviceMem in(sizeof(InDataType) * num_elements);
SimpleDeviceMem out(sizeof(OutDataType) * num_elements);
@@ -82,8 +82,8 @@ int main(int argc, char* argv[])
auto argument_ptr = op_ptr->MakeArgumentPointer(in_lengths,
in_strides,
reduce_dims,
&alpha,
&beta,
alpha,
beta,
in.GetDeviceBuffer(),
out.GetDeviceBuffer(),
PassThrough{},
@@ -129,8 +129,8 @@ int main(int argc, char* argv[])
auto argument_ptr = op_ptr->MakeArgumentPointer(in_lengths,
in_strides,
reduce_dims,
&alpha,
&beta,
alpha,
beta,
in.GetDeviceBuffer(),
out.GetDeviceBuffer(),
PassThrough{},
@@ -147,4 +147,4 @@ int main(int argc, char* argv[])
}
return 0;
}
}

4
client_example/15_reduce/reduce_nhwc_c.cpp
View File

@@ -61,8 +61,8 @@ int main(int argc, char* argv[])
for(auto dim : reduce_dims)
reduce_length *= in_lengths[dim];
float alpha{1.0f};
float beta{0.0f};
double alpha{1.0};
double beta{0.0};
SimpleDeviceMem in(sizeof(InDataType) * num_in_elements);
SimpleDeviceMem out(sizeof(OutDataType) * num_out_elements);

8
example/12_reduce/reduce_blockwise_impl.hpp
View File

@@ -267,8 +267,8 @@ int reduce_blockwise_impl(bool do_verification,
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in.mData.data(),
nullptr,
out_ref.mData.data(),
@@ -295,8 +295,8 @@ int reduce_blockwise_impl(bool do_verification,
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in_dev.GetDeviceBuffer(),
nullptr,
out_dev.GetDeviceBuffer(),

12
example/12_reduce/reduce_blockwise_two_call.cpp
View File

@@ -226,8 +226,8 @@ int main(int argc, char* argv[])
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in_1.mData.data(),
nullptr,
out_ref.mData.data(),
@@ -254,8 +254,8 @@ int main(int argc, char* argv[])
arrInLengths_2,
arrInStrides_2,
reduceDims_1,
1.0f,
0.0f,
1.0,
0.0,
in_1_dev.GetDeviceBuffer(),
nullptr,
in_2_dev.GetDeviceBuffer(),
@@ -278,8 +278,8 @@ int main(int argc, char* argv[])
arrOutLengths,
arrOutStrides,
reduceDims_2,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in_2_dev.GetDeviceBuffer(),
nullptr,
out_dev.GetDeviceBuffer(),

8
example/12_reduce/reduce_multiblock_atomic_add_impl.hpp
View File

@@ -180,8 +180,8 @@ int reduce_multiblock_atomic_add_impl(bool do_verification,
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in.mData.data(),
nullptr,
out_ref.mData.data(),
@@ -208,8 +208,8 @@ int reduce_multiblock_atomic_add_impl(bool do_verification,
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in_dev.GetDeviceBuffer(),
nullptr,
out_dev.GetDeviceBuffer(),

12
example/23_softmax/softmax_blockwise.cpp
View File

@@ -56,8 +56,8 @@ class SimpleAppArgs
int option_index = 0;
public:
std::vector<size_t> inLengths = {8, 128, 2048};
std::vector<AccDataType> scales = {2.0f, 2.0f};
std::vector<size_t> inLengths = {8, 128, 2048};
std::vector<double> scales = {2.0, 2.0};
bool do_verification = true;
int init_method = 2;
@@ -151,8 +151,8 @@ int main(int argc, char* argv[])
auto inStrides = in.mDesc.GetStrides();
auto outStrides = out.mDesc.GetStrides();
AccDataType alpha = args.scales[0];
AccDataType beta = args.scales[1];
double alpha = args.scales[0];
double beta = args.scales[1];
std::cout << "in: " << in.mDesc << std::endl;
std::cout << "out: " << out.mDesc << std::endl;
@@ -221,8 +221,8 @@ int main(int argc, char* argv[])
auto argument_ptr = device_instance.MakeArgumentPointer(i_inLengths,
i_inStrides,
reduceDims,
&alpha,
&beta,
alpha,
beta,
in_dev.GetDeviceBuffer(),
out_dev.GetDeviceBuffer(),
PassThrough{},

8
example/33_multiple_reduce/dual_reduce_common.hpp
View File

@@ -217,8 +217,8 @@ int mean_meansquare_dual_reduce_test(size_t n,
size_t invariant_total_length = n;
size_t reduce_total_length = h * w * c;
const AccDataType alpha = ck::type_convert<AccDataType>(1.0f);
const AccDataType beta = ck::type_convert<AccDataType>(0.0f);
const double alpha = 1.0f;
const double beta = 0.0f;
std::size_t num_thread = 1;
@@ -267,8 +267,8 @@ int mean_meansquare_dual_reduce_test(size_t n,
i_outLengths,
{i_outStrides, i_outStrides},
reduceDims,
{&alpha, &alpha},
{&beta, &beta},
{alpha, alpha},
{beta, beta},
in_dev.GetDeviceBuffer(),
{mean_dev.GetDeviceBuffer(), meansquare_dev.GetDeviceBuffer()},
ck::make_tuple(InElementwiseOperation_Mean{}, InElementwiseOperation_Meansquare{}),

2
include/ck/tensor_operation/gpu/device/device_elementwise_normalization.hpp
View File

@@ -32,7 +32,7 @@ struct DeviceElementwiseNormalization : public BaseOperator
const std::vector<index_t> betaStrides,
const std::vector<index_t> yStrides,
const std::vector<index_t> reduceDims,
AccDataType epsilon,
double epsilon,
const std::array<const void*, NumInput> in_dev_buffers,
const void* p_gamma,
const void* p_beta,

4
include/ck/tensor_operation/gpu/device/device_multiple_reduce.hpp
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@@ -32,8 +32,8 @@ struct DeviceMultipleReduce : public BaseOperator
const std::array<index_t, NumOutputDim> outLengths,
const std::array<std::array<index_t, NumOutputDim>, NumReduction> outStrides,
const std::array<int, NumReduceDim> reduceDims,
const std::array<const void*, NumReduction> alphas,
const std::array<const void*, NumReduction> betas,
const std::array<double, NumReduction> alphas,
const std::array<double, NumReduction> betas,
const void* in_dev,
const std::array<void*, NumReduction> out_dev_buffers,
const InElementwiseOperationTuple in_elementwise_op_tuple,

2
include/ck/tensor_operation/gpu/device/device_normalization.hpp
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@@ -28,7 +28,7 @@ struct DeviceNormalization : public BaseOperator
const std::vector<index_t> betaStrides,
const std::vector<index_t> yStrides,
const std::vector<index_t> reduceDims,
AccDataType epsilon,
double epsilon,
const void* p_x,
const void* p_gamma,
const void* p_beta,

4
include/ck/tensor_operation/gpu/device/device_reduce.hpp
View File

@@ -33,8 +33,8 @@ struct DeviceReduce : public BaseOperator
const std::array<index_t, NumOutDim> outLengths,
const std::array<index_t, NumOutDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const void* in_dev,
const void* in_index_dev,
void* out_dev,

10
include/ck/tensor_operation/gpu/device/device_softmax.hpp
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@@ -27,10 +27,8 @@ struct DeviceSoftmax : public BaseOperator
// @param[in] inLengths Input tensor extent(s) from high to low dimension
// @param[in] inStrides Input tensor stride(s) from high to low dimension
// @param[in] reduceDims The dimension(s) the normalization operation is applied
// @param[in] alpha Typeless pointer in host memory storing the alpha scaling
// value as type AccDataType
// @param[in] beta Typeless pointer in host memory storing the beta scaling
// value as type AccDataType
// @param[in] alpha double type value
// @param[in] beta double type value
// @param[in] in_dev Typeless const pointer in device memory storing the input
// tensor
// @param out_dev Typeless pointer in device memory storing the output tensor
@@ -43,8 +41,8 @@ struct DeviceSoftmax : public BaseOperator
MakeArgumentPointer(const std::vector<index_t> inLengths,
const std::vector<index_t> inStrides,
const std::vector<int> reduceDims,
const void* alpha,
const void* beta,
double alpha,
double beta,
const void* in_dev,
void* out_dev,
InElementwiseOp in_elementwise_op,

8
include/ck/tensor_operation/gpu/device/impl/device_elementwise_normalization_impl.hpp
View File

@@ -270,18 +270,18 @@ struct DeviceElementwiseNormalizationImpl
const std::vector<index_t> reduceDims,
XElementwiseOperation x_elementwise_op,
YElementwiseOperation y_elementwise_op,
AccDataType epsilon,
double epsilon,
const std::array<const void*, NumInput> in_dev_buffers,
const GammaDataType* p_gamma,
const BetaDataType* p_beta,
YDataType* p_y)
: epsilon_(epsilon),
p_gamma_(p_gamma),
: p_gamma_(p_gamma),
p_beta_(p_beta),
p_y_(p_y),
x_elementwise_op_(x_elementwise_op),
y_elementwise_op_(y_elementwise_op)
{
epsilon_ = static_cast<AccDataType>(epsilon);
Lengths_ = shuffle_tensor_dimensions<Rank, NumReduceDim>(lengths, reduceDims);
for(int i = 0; i < NumInput; i++)
@@ -543,7 +543,7 @@ struct DeviceElementwiseNormalizationImpl
const std::vector<index_t> betaStrides,
const std::vector<index_t> yStrides,
const std::vector<index_t> reduceDims,
AccDataType epsilon,
double epsilon,
const std::array<const void*, NumInput> in_dev_buffers,
const void* p_gamma,
const void* p_beta,

12
include/ck/tensor_operation/gpu/device/impl/device_multiple_reduce_multiblock.hpp
View File

@@ -270,8 +270,8 @@ struct DeviceMultipleReduceMultiBlock : public DeviceMultipleReduce<Rank,
const std::array<index_t, NumOutputDim>& outLengths,
const std::array<std::array<index_t, NumOutputDim>, NumReduction>& outStridesArray,
const std::array<int, NumReduceDim>& reduceDims,
const std::array<const void*, NumReduction>& alphas,
const std::array<const void*, NumReduction>& betas,
const std::array<double, NumReduction>& alphas,
const std::array<double, NumReduction>& betas,
const void* in_dev,
const std::array<void*, NumReduction>& out_dev_buffers,
const InElementwiseOperationTuple in_elementwise_op_tuple,
@@ -286,8 +286,8 @@ struct DeviceMultipleReduceMultiBlock : public DeviceMultipleReduce<Rank,
for(size_t i = 0; i < NumReduction; i++)
{
alpha_values_(i) = *static_cast<const AccDataType*>(alphas[i]);
beta_values_(i) = *static_cast<const AccDataType*>(betas[i]);
alpha_values_(i) = static_cast<AccDataType>(alphas[i]);
beta_values_(i) = static_cast<AccDataType>(betas[i]);
};
in_dev_ = static_cast<const InDataType*>(in_dev);
@@ -547,8 +547,8 @@ struct DeviceMultipleReduceMultiBlock : public DeviceMultipleReduce<Rank,
const std::array<index_t, NumOutputDim> outLengths,
const std::array<std::array<index_t, NumOutputDim>, NumReduction> outStridesArray,
const std::array<int, NumReduceDim> reduceDims,
const std::array<const void*, NumReduction> alphas,
const std::array<const void*, NumReduction> betas,
const std::array<double, NumReduction> alphas,
const std::array<double, NumReduction> betas,
const void* in_dev,
const std::array<void*, NumReduction> out_dev_buffers,
const InElementwiseOperationTuple in_elementwise_op_tuple,

12
include/ck/tensor_operation/gpu/device/impl/device_multiple_reduce_threadwise.hpp
View File

@@ -195,8 +195,8 @@ struct DeviceMultipleReduceThreadWise : public DeviceMultipleReduce<Rank,
const std::array<index_t, NumOutputDim>& outLengths,
const std::array<std::array<index_t, NumOutputDim>, NumReduction>& outStridesArray,
const std::array<int, NumReduceDim>& reduceDims,
const std::array<const void*, NumReduction>& alphas,
const std::array<const void*, NumReduction>& betas,
const std::array<double, NumReduction>& alphas,
const std::array<double, NumReduction>& betas,
const void* in_dev,
const std::array<void*, NumReduction>& out_dev_buffers,
const InElementwiseOperationTuple in_elementwise_op_tuple,
@@ -211,8 +211,8 @@ struct DeviceMultipleReduceThreadWise : public DeviceMultipleReduce<Rank,
for(size_t i = 0; i < NumReduction; i++)
{
alpha_values_(i) = *static_cast<const AccDataType*>(alphas[i]);
beta_values_(i) = *static_cast<const AccDataType*>(betas[i]);
alpha_values_(i) = static_cast<AccDataType>(alphas[i]);
beta_values_(i) = static_cast<AccDataType>(betas[i]);
};
in_dev_ = static_cast<const InDataType*>(in_dev);
@@ -374,8 +374,8 @@ struct DeviceMultipleReduceThreadWise : public DeviceMultipleReduce<Rank,
const std::array<index_t, NumOutputDim> outLengths,
const std::array<std::array<index_t, NumOutputDim>, NumReduction> outStridesArray,
const std::array<int, NumReduceDim> reduceDims,
const std::array<const void*, NumReduction> alphas,
const std::array<const void*, NumReduction> betas,
const std::array<double, NumReduction> alphas,
const std::array<double, NumReduction> betas,
const void* in_dev,
const std::array<void*, NumReduction> out_dev_buffers,
const InElementwiseOperationTuple in_elementwise_op_tuple,

9
include/ck/tensor_operation/gpu/device/impl/device_normalization_impl.hpp
View File

@@ -221,18 +221,19 @@ struct DeviceNormalizationImpl : public DeviceNormalization<XDataType,
const std::vector<index_t> yStrides,
const std::vector<index_t> reduceDims,
AccElementwiseOperation acc_elementwise_op,
AccDataType epsilon,
double epsilon,
const XDataType* p_x,
const GammaDataType* p_gamma,
const BetaDataType* p_beta,
YDataType* p_y)
: epsilon_(epsilon),
p_x_(p_x),
: p_x_(p_x),
p_gamma_(p_gamma),
p_beta_(p_beta),
p_y_(p_y),
acc_elementwise_op_(acc_elementwise_op)
{
epsilon_ = static_cast<AccDataType>(epsilon);
Lengths_ = shuffle_tensor_dimensions<Rank, NumReduceDim>(lengths, reduceDims);
xStrides_ = shuffle_tensor_dimensions<Rank, NumReduceDim>(xStrides, reduceDims);
yStrides_ = shuffle_tensor_dimensions<Rank, NumReduceDim>(yStrides, reduceDims);
@@ -421,7 +422,7 @@ struct DeviceNormalizationImpl : public DeviceNormalization<XDataType,
const std::vector<index_t> betaStrides,
const std::vector<index_t> yStrides,
const std::vector<index_t> reduceDims,
AccDataType epsilon,
double epsilon,
const void* p_x,
const void* p_gamma,
const void* p_beta,

8
include/ck/tensor_operation/gpu/device/impl/device_reduce_multiblock.hpp
View File

@@ -217,8 +217,8 @@ struct DeviceReduceMultiBlock : public DeviceReduce<InDataType,
const std::array<index_t, NumDstDim> outLengths,
const std::array<index_t, NumDstDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const InDataType* in_dev,
const IndexDataType* in_index_dev,
OutDataType* out_dev,
@@ -502,8 +502,8 @@ struct DeviceReduceMultiBlock : public DeviceReduce<InDataType,
const std::array<index_t, NumDstDim> outLengths,
const std::array<index_t, NumDstDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const void* in_dev,
const void* in_index_dev,
void* out_dev,

8
include/ck/tensor_operation/gpu/device/impl/device_reduce_threadwise.hpp
View File

@@ -165,8 +165,8 @@ struct DeviceReduceThreadWise : public DeviceReduce<InDataType,
const std::array<index_t, NumDstDim> outLengths,
const std::array<index_t, NumDstDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const InDataType* in_dev,
OutDataType* out_dev,
IndexDataType* out_index_dev,
@@ -341,8 +341,8 @@ struct DeviceReduceThreadWise : public DeviceReduce<InDataType,
const std::array<index_t, NumDstDim> outLengths,
const std::array<index_t, NumDstDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const void* in_dev,
const void* in_index_dev,
void* out_dev,

23
include/ck/tensor_operation/gpu/device/impl/device_softmax_impl.hpp
View File

@@ -156,19 +156,20 @@ struct DeviceSoftmaxImpl : public DeviceSoftmax<InDataType,
Argument(const std::vector<index_t> inLengths,
const std::vector<index_t> inStrides,
const std::vector<index_t> reduceDims,
AccDataType alpha,
AccDataType beta,
double alpha,
double beta,
const InDataType* in_dev,
OutDataType* out_dev,
InElementwiseOp in_elementwise_op,
AccElementwiseOp acc_elementwise_op)
: alpha_{alpha},
beta_{beta},
in_dev_{in_dev},
: in_dev_{in_dev},
out_dev_{out_dev},
in_elementwise_op_{in_elementwise_op},
acc_elementwise_op_{acc_elementwise_op}
{
alpha_ = static_cast<AccDataType>(alpha);
beta_ = static_cast<AccDataType>(beta);
if(Rank != inLengths.size() || Rank != inStrides.size() ||
NumReduceDim != reduceDims.size())
{
@@ -336,8 +337,8 @@ struct DeviceSoftmaxImpl : public DeviceSoftmax<InDataType,
static auto MakeArgument(const std::vector<index_t> inLengths,
const std::vector<index_t> inStrides,
const std::vector<int> reduceDims,
const AccDataType alpha,
const AccDataType beta,
double alpha,
double beta,
const InDataType* in_dev,
OutDataType* out_dev,
InElementwiseOp in_elementwise_op,
@@ -375,8 +376,8 @@ struct DeviceSoftmaxImpl : public DeviceSoftmax<InDataType,
std::unique_ptr<BaseArgument> MakeArgumentPointer(const std::vector<index_t> inLengths,
const std::vector<index_t> inStrides,
const std::vector<int> reduceDims,
const void* alpha,
const void* beta,
double alpha,
double beta,
const void* in_dev,
void* out_dev,
InElementwiseOp in_elementwise_op,
@@ -385,8 +386,8 @@ struct DeviceSoftmaxImpl : public DeviceSoftmax<InDataType,
return std::make_unique<Argument>(inLengths,
inStrides,
reduceDims,
*static_cast<const AccDataType*>(alpha),
*static_cast<const AccDataType*>(beta),
alpha,
beta,
static_cast<const InDataType*>(in_dev),
static_cast<OutDataType*>(out_dev),
in_elementwise_op,

8
library/include/ck/library/reference_tensor_operation/cpu/reference_reduce.hpp
View File

@@ -56,8 +56,8 @@ struct ReferenceReduce : public device::DeviceReduce<InDataType,
const std::array<index_t, NumDstDim> outLengths,
const std::array<index_t, NumDstDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const InDataType* in_host,
OutDataType* out_host,
IndexDataType* out_index_host,
@@ -388,8 +388,8 @@ struct ReferenceReduce : public device::DeviceReduce<InDataType,
const std::array<index_t, NumDstDim> outLengths,
const std::array<index_t, NumDstDim> outStrides,
const std::array<int, NumReduceDim> reduceDims,
float alpha,
float beta,
double alpha,
double beta,
const void* in_host,
const void* in_index_host,
void* out_host,

13
library/include/ck/library/reference_tensor_operation/cpu/reference_softmax.hpp
View File

@@ -24,11 +24,14 @@ struct ReferenceSoftmax : public device::BaseOperator
{
Argument(const Tensor<InDataType>& in,
Tensor<OutDataType>& out,
AccDataType alpha,
AccDataType beta,
double alpha,
double beta,
const std::vector<index_t> sm_reduce_dims)
: in_(in), out_(out), alpha_(alpha), beta_(beta), sm_reduce_dims_(sm_reduce_dims)
: in_(in), out_(out), sm_reduce_dims_(sm_reduce_dims)
{
alpha_ = static_cast<AccDataType>(alpha);
beta_ = static_cast<AccDataType>(beta);
// std::cout << "debug: scalar dims: ";
for(size_t i = 0; i < in.mDesc.GetNumOfDimension(); i++)
{
@@ -143,8 +146,8 @@ struct ReferenceSoftmax : public device::BaseOperator
static auto MakeArgument(const Tensor<InDataType>& in,
Tensor<OutDataType>& out,
AccDataType alpha,
AccDataType beta,
double alpha,
double beta,
const std::vector<index_t> sm_reduce_dims)
{
return Argument{in, out, alpha, beta, sm_reduce_dims};

8
profiler/include/profiler/profile_reduce_impl.hpp
View File

@@ -332,8 +332,8 @@ bool profile_reduce_impl_impl(bool do_verification,
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in.mData.data(),
nullptr,
out_ref.mData.data(),
@@ -361,8 +361,8 @@ bool profile_reduce_impl_impl(bool do_verification,
arrOutLengths,
arrOutStrides,
reduceDims,
alpha,
beta,
static_cast<double>(alpha),
static_cast<double>(beta),
in_dev.GetDeviceBuffer(),
nullptr,
out_dev.GetDeviceBuffer(),

8
profiler/include/profiler/profile_softmax_impl.hpp
View File

@@ -48,8 +48,8 @@ bool profile_softmax_impl(int do_verification,
std::vector<index_t> in_length,
std::vector<index_t> in_strides,
std::vector<index_t> reduce_dims,
AccDataType alpha,
AccDataType beta)
double alpha,
double beta)
{
if(Rank != in_length.size())
{
@@ -122,8 +122,8 @@ bool profile_softmax_impl(int do_verification,
auto argument_ptr = inst_ptr->MakeArgumentPointer(in_tensor_lengths,
in_tensor_strides,
reduce_dims,
&alpha,
&beta,
alpha,
beta,
in_dev.GetDeviceBuffer(),
out_dev.GetDeviceBuffer(),
PassThrough{},

16
profiler/src/profile_softmax.cpp
View File

@@ -99,8 +99,8 @@ int profile_softmax(int argc, char* argv[])
length,
stride,
reduce,
float(alpha),
float(beta));
double(alpha),
double(beta));
}
else if(data_type == SoftmaxDataType::F32_F32)
{
@@ -111,8 +111,8 @@ int profile_softmax(int argc, char* argv[])
length,
stride,
reduce,
float(alpha),
float(beta));
double(alpha),
double(beta));
}
else
{
@@ -131,8 +131,8 @@ int profile_softmax(int argc, char* argv[])
length,
stride,
reduce,
float(alpha),
float(beta));
double(alpha),
double(beta));
}
else if(data_type == SoftmaxDataType::F32_F32)
{
@@ -143,8 +143,8 @@ int profile_softmax(int argc, char* argv[])
length,
stride,
reduce,
float(alpha),
float(beta));
double(alpha),
double(beta));
}
else
{