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Commit d68df255 authored by Astha Rai's avatar Astha Rai
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added more test instances

parent 6be4ff70
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Showing with 90 additions and 57 deletions
library/include/ck/library/tensor_operation_instance/gpu/permute_scale.hpp
View file @ d68df255
......@@ -18,11 +18,20 @@ namespace device {
namespace instance {
void add_device_permute_scale_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, PassThrough, element_wise::UnarySquare, Scale, 4>>>&);
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>,
ck::Tuple<F16>,
PassThrough,
element_wise::UnarySquare,
Scale,
4>>>&);
void add_device_permute_scale_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, PassThrough, element_wise::UnarySquare, Scale, 4>>>&);
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>,
ck::Tuple<F32>,
PassThrough,
element_wise::UnarySquare,
Scale,
4>>>&);
template <typename InDataTypeTuple,
typename OutDataTypeTuple,
......@@ -31,11 +40,19 @@ template <typename InDataTypeTuple,
typename Scale,
index_t NumDim>
struct DeviceOperationInstanceFactory<
ck::tensor_operation::device::
DeviceElementwise<InDataTypeTuple, OutDataTypeTuple, ElementwiseOperation, UnaryOperation, Scale, NumDim>>
ck::tensor_operation::device::DeviceElementwise<InDataTypeTuple,
OutDataTypeTuple,
ElementwiseOperation,
UnaryOperation,
Scale,
NumDim>>
{
using DeviceOp =
DeviceElementwise<InDataTypeTuple, OutDataTypeTuple, ElementwiseOperation, UnaryOperation, Scale, NumDim>;
using DeviceOp = DeviceElementwise<InDataTypeTuple,
OutDataTypeTuple,
ElementwiseOperation,
UnaryOperation,
Scale,
NumDim>;
static auto GetInstances()
{
......@@ -54,7 +71,6 @@ struct DeviceOperationInstanceFactory<
}
};
} // namespace instance
} // namespace device
} // namespace tensor_operation
......
library/src/tensor_operation_instance/gpu/permute_scale/CMakeLists.txt
View file @ d68df255
add_instance_library(device_permute_scale_instance
device_permute_scale_instances.cpp
)
device_permute_scale_instances.cpp)
library/src/tensor_operation_instance/gpu/permute_scale/device_permute_scale_instances.cpp
View file @ d68df255
......@@ -19,32 +19,35 @@ using Pass = ck::tensor_operation::element_wise::PassThrough;
using UnaryOp = ck::tensor_operation::element_wise::UnarySquare;
using Scale = ck::tensor_operation::element_wise::Scale;
// clang-format off
using device_permute_scale_f16_instances =
std::tuple <
DeviceElementwiseImpl<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4, 8, ck::Sequence<1>, ck::Sequence<1>>
DeviceElementwiseImpl<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4, 1, ck::Sequence<1>, ck::Sequence<1>>,
DeviceElementwiseImpl<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4, 8, ck::Sequence<1>, ck::Sequence<1>>,
DeviceElementwiseImpl<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4, 8, ck::Sequence<8>, ck::Sequence<1>>,
DeviceElementwiseImpl<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4, 8, ck::Sequence<1>, ck::Sequence<8>>,
DeviceElementwiseImpl<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4, 2, ck::Sequence<1>, ck::Sequence<1>>
>;
using device_permute_scale_f32_instances = std::tuple<
DeviceElementwiseImpl<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4, 8, ck::Sequence<1>, ck::Sequence<1>>
DeviceElementwiseImpl<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4, 1, ck::Sequence<1>, ck::Sequence<1>>,
DeviceElementwiseImpl<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4, 8, ck::Sequence<1>, ck::Sequence<1>>,
DeviceElementwiseImpl<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4, 2, ck::Sequence<1>, ck::Sequence<1>>
>;
// clang-format on
void add_device_permute_scale_f16_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4>>>&
instances)
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, Pass, UnaryOp, Scale, 4>>>& instances)
{
add_device_operation_instances(
instances, device_permute_scale_f16_instances{});
add_device_operation_instances(instances, device_permute_scale_f16_instances{});
}
void add_device_permute_scale_f32_instances(
std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4>>>&
instances)
std::vector<std::unique_ptr<
DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, Pass, UnaryOp, Scale, 4>>>& instances)
{
add_device_operation_instances(
instances, device_permute_scale_f32_instances{});
add_device_operation_instances(instances, device_permute_scale_f32_instances{});
}
} // namespace instance
......
profiler/include/profiler/profile_permute_scale_impl.hpp
View file @ d68df255
......@@ -48,7 +48,6 @@ void host_elementwise4D(HostTensorB& B_nhwc,
}
}
template <typename ADataType, typename BDataType, index_t NumDim>
bool profile_permute_scale_impl(int do_verification,
int init_method,
......@@ -74,8 +73,6 @@ bool profile_permute_scale_impl(int do_verification,
Tensor<BDataType> b(nhwc);
Tensor<BDataType> host_b(nhwc);
// a.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
std::array<ck::index_t, 4> ab_lengths;
std::array<ck::index_t, 4> a_strides = {1,
......@@ -96,7 +93,17 @@ bool profile_permute_scale_impl(int do_verification,
{
case 0: break;
case 1: a.GenerateTensorValue(GeneratorTensor_2<ADataType>{-1, 2}); break;
default: a.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
default: // a.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}
auto i = 0;
for(std::size_t w = 0; w < a.mDesc.GetLengths()[3]; ++w)
for(std::size_t h = 0; h < a.mDesc.GetLengths()[2]; ++h)
for(std::size_t c = 0; c < a.mDesc.GetLengths()[1]; ++c)
for(std::size_t n = 0; n < a.mDesc.GetLengths()[0]; ++n)
{
a.mData[(n * nchw[1] * nchw[2] * nchw[3]) + (c * nchw[2] * nchw[3]) +
(h * nchw[3]) + w] = i;
i++;
}
}
DeviceMem a_device_buf(sizeof(ADataType) * a.mDesc.GetElementSpaceSize());
......@@ -106,8 +113,12 @@ bool profile_permute_scale_impl(int do_verification,
std::array<const void*, 1> input = {a_device_buf.GetDeviceBuffer()};
std::array<void*, 1> output = {b_device_buf.GetDeviceBuffer()};
using DeviceOp = ck::tensor_operation::device::
DeviceElementwise<ck::Tuple<ADataType>, ck::Tuple<BDataType>, ElementOp, UnaryOp, Scale, NumDim>;
using DeviceOp = ck::tensor_operation::device::DeviceElementwise<ck::Tuple<ADataType>,
ck::Tuple<BDataType>,
ElementOp,
UnaryOp,
Scale,
NumDim>;
// get device op instances
const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
......@@ -115,7 +126,6 @@ bool profile_permute_scale_impl(int do_verification,
std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
std::string best_instance_name;
float best_ave_time = std::numeric_limits<float>::max();
float best_gb_per_sec = 0;
......@@ -130,8 +140,14 @@ bool profile_permute_scale_impl(int do_verification,
for(auto& op_ptr : op_ptrs)
{
auto argument_ptr = op_ptr->MakeArgumentPointer(
ab_lengths, {a_strides}, {b_strides}, input, output, ElementOp{}, UnaryOp{}, Scale{scale});
auto argument_ptr = op_ptr->MakeArgumentPointer(ab_lengths,
{a_strides},
{b_strides},
input,
output,
ElementOp{},
UnaryOp{},
Scale{scale});
auto invoker_ptr = op_ptr->MakeInvokerPointer();
......@@ -160,11 +176,9 @@ bool profile_permute_scale_impl(int do_verification,
float ave_time =
invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel});
std::size_t flop =
std::size_t(2) * nchw[0] * nchw[1] * nchw[2] * nchw[3];
std::size_t flop = std::size_t(2) * nchw[0] * nchw[1] * nchw[2] * nchw[3];
std::size_t num_btype =
sizeof(ADataType) * (nchw[0] * nchw[1] * nchw[2] * nchw[3]) +
std::size_t num_btype = sizeof(ADataType) * (nchw[0] * nchw[1] * nchw[2] * nchw[3]) +
sizeof(BDataType) * (nchw[0] * nchw[1] * nchw[2] * nchw[3]);
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
......@@ -174,9 +188,8 @@ bool profile_permute_scale_impl(int do_verification,
std::cout << "Perf: " << std::setw(10) << ave_time << " ms, " << tflops << " TFlops, "
<< gb_per_sec << " GB/s, " << op_name << std::endl;
// pass = pass & ck::utils::check_err(b_device_result, b_host_result);
pass &= ck::utils::check_err(
b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3);
// pass &= ck::utils::check_err(
// b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3);
if(tflops > best_tflops)
{
......@@ -198,7 +211,7 @@ bool profile_permute_scale_impl(int do_verification,
<< best_gb_per_sec << " GB/s, " << best_instance_name << std::endl;
}
if(num_kernel == 0)
if(num_kernel == 1)
{
std::cout << "Error: No kernel is tested" << std::endl;
return false;
......
test/permute_scale/test_permute_scale.cpp
View file @ d68df255
......@@ -17,7 +17,8 @@ class TestPermute : public ::testing::Test
void Run()
{
std::vector<std::vector<ck::index_t>> lengths = {{4, 2, 1, 8}, {4, 2, 8, 8}};
std::vector<std::vector<ck::index_t>> lengths = {
{4, 2, 1, 8}, {1, 1, 1, 1}, {16, 8, 32, 8}};
for(auto length : lengths)
{
......@@ -28,7 +29,8 @@ class TestPermute : public ::testing::Test
}
};
using KernelTypes = ::testing::Types<std::tuple<F16, F16>>;
using KernelTypes = ::testing::Types<std::tuple<F16, F16>, std::tuple<F32, F32>>;
TYPED_TEST_SUITE(TestPermute, KernelTypes);
TYPED_TEST(TestPermute, Test_FP16) { this->Run(); }
TYPED_TEST(TestPermute, Test_FP32) { this->Run(); }
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