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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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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
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@@ -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{}),