Files
composable_kernel/test/convnd_fwd/conv2d_fwd.cpp
Adam Osewski 71b19b4e4e Fix return type to be conformant with CTest. (#160)
Co-authored-by: Adam Osewski <aosewski@amd.com>

[ROCm/composable_kernel commit: 982f8bbc29]
2022-03-30 20:05:20 -05:00

148 lines
5.9 KiB
C++

#include <half.hpp>
#include <iostream>
#include <stdexcept>
#include <tuple>
#include <vector>
#include "data_type.hpp"
#include "element_wise_operation.hpp"
#include "conv_test_util.hpp"
#include "host_tensor.hpp"
#include "tensor_layout.hpp"
#include "test_util.hpp"
// Forward declarations for conv instances.
using DeviceConvFwdNoOpPtr =
ck::tensor_operation::device::DeviceConvFwdPtr<ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>;
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_conv2d_fwd_instance {
void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_instances(
std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances(std::vector<DeviceConvFwdNoOpPtr>&);
} // namespace device_conv2d_fwd_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
namespace {
bool TestConv2DNHWC()
{
bool res{true};
ck::conv_util::ConvParams params;
params.N = 2;
params.K = 16;
params.C = 4;
params.input_spatial_lengths = std::vector<ck::index_t>{16, 16};
params.conv_filter_strides = std::vector<ck::index_t>{1, 1};
auto host_tensors = test::conv::GetHostTensors(params);
const Tensor<float>& input = std::get<0>(host_tensors);
const Tensor<float>& weights = std::get<1>(host_tensors);
Tensor<float>& host_output = std::get<2>(host_tensors);
Tensor<float>& device_output = std::get<3>(host_tensors);
test::conv::RunReferenceConv<2>(params, input, weights, host_output);
test::conv::RunConv<2>(params, input, weights, device_output);
res = res &&
test::check_err(
device_output.mData, host_output.mData, "Error: incorrect results!", 1e-5f, 1e-4f);
return res;
}
template <typename T>
bool TestConv2DNHWCInstances(const std::vector<DeviceConvFwdNoOpPtr>& conv_ptrs)
{
ck::conv_util::ConvParams params;
params.num_dim_spatial = 2;
params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3};
params.input_spatial_lengths = std::vector<ck::index_t>{71, 71};
params.conv_filter_strides = std::vector<ck::index_t>{2, 2};
params.conv_filter_dilations = std::vector<ck::index_t>{1, 1};
params.input_left_pads = std::vector<ck::index_t>{1, 1};
params.input_right_pads = std::vector<ck::index_t>{1, 1};
auto host_tensors = test::conv::GetHostTensors<T,
T,
T,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>(params);
const Tensor<T>& input = std::get<0>(host_tensors);
const Tensor<T>& weights = std::get<1>(host_tensors);
Tensor<T>& host_output = std::get<2>(host_tensors);
Tensor<T>& device_output = std::get<3>(host_tensors);
test::conv::RunReferenceConv<2>(params, input, weights, host_output);
return test::conv::RunConvInstances<2>(
params, conv_ptrs, input, weights, device_output, host_output);
}
bool TestConv2DNHWCBF16Instances()
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
ck::tensor_operation::device::device_conv2d_fwd_instance::
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances(conv_ptrs);
return TestConv2DNHWCInstances<ck::bhalf_t>(conv_ptrs);
}
bool TestConv2DNHWCF16Instances()
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
ck::tensor_operation::device::device_conv2d_fwd_instance::
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances(conv_ptrs);
ck::tensor_operation::device::device_conv2d_fwd_instance::
add_device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_instances(conv_ptrs);
return TestConv2DNHWCInstances<ck::half_t>(conv_ptrs);
}
bool TestConv2DNHWCF32Instances()
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
ck::tensor_operation::device::device_conv2d_fwd_instance::
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances(conv_ptrs);
return TestConv2DNHWCInstances<float>(conv_ptrs);
}
bool TestConv2DNHWCInt8Instances()
{
std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
ck::tensor_operation::device::device_conv2d_fwd_instance::
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances(conv_ptrs);
return TestConv2DNHWCInstances<int8_t>(conv_ptrs);
}
} // anonymous namespace
int main()
{
bool res{true};
res = TestConv2DNHWC();
std::cout << "TestConv2DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = TestConv2DNHWCBF16Instances();
std::cout << "\nTestConv2DNHWCBF16Instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = TestConv2DNHWCF16Instances();
std::cout << "\nTestConv2DNHWCF16Instances ....." << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = TestConv2DNHWCF32Instances();
std::cout << "\nTestConv2DNHWCF32Instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
res = TestConv2DNHWCInt8Instances();
std::cout << "\nTestConv2DNHWCInt8Instances ..... " << (res ? "SUCCESS" : "FAILURE")
<< std::endl;
return res ? 0 : 1;
}