cutlass/test/unit/core/numeric_conversion.cu

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/***************************************************************************************************
2021-02-26 22:58:26 +08:00
* Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
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* conditions and the following disclaimer.
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* conditions and the following disclaimer in the documentation and/or other materials
* provided with the distribution.
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**************************************************************************************************/
/*! \file
\brief Unit tests for conversion operators.
*/
#include "../common/cutlass_unit_test.h"
#include "cutlass/numeric_conversion.h"
#include "cutlass/layout/matrix.h"
#include "cutlass/util/host_tensor.h"
/////////////////////////////////////////////////////////////////////////////////////////////////
namespace test {
namespace core {
namespace kernel {
/////////////////////////////////////////////////////////////////////////////////////////////////
/// Conversion template
template <typename Destination, typename Source, int Count>
__global__ void convert(
cutlass::Array<Destination, Count> *destination,
cutlass::Array<Source, Count> const *source) {
cutlass::NumericArrayConverter<Destination, Source, Count> convert;
*destination = convert(*source);
}
/////////////////////////////////////////////////////////////////////////////////////////////////
} // namespace kernel
} // namespace core
} // namespace test
/////////////////////////////////////////////////////////////////////////////////////////////////
TEST(NumericConversion, f32_to_f16_rn) {
int const kN = 1;
using Source = float;
using Destination = cutlass::half_t;
dim3 grid(1, 1);
dim3 block(1, 1);
cutlass::HostTensor<cutlass::half_t, cutlass::layout::RowMajor> destination({1, kN});
cutlass::HostTensor<float, cutlass::layout::RowMajor> source({1, kN});
for (int i = 0; i < kN; ++i) {
source.host_data()[i] = float(i);
}
source.sync_device();
test::core::kernel::convert<Destination, Source, 1><<< grid, block >>>(
reinterpret_cast<cutlass::Array<Destination, 1> *>(destination.device_data()),
reinterpret_cast<cutlass::Array<Source, 1> const *>(source.device_data())
);
destination.sync_host();
for (int i = 0; i < kN; ++i) {
EXPECT_TRUE(float(destination.host_data()[i]) == source.host_data()[i]);
}
}
TEST(NumericConversion, f32x8_to_f16x8_rn) {
int const kN = 8;
using Source = float;
using Destination = cutlass::half_t;
dim3 grid(1, 1);
dim3 block(1, 1);
cutlass::HostTensor<Destination, cutlass::layout::RowMajor> destination({1, kN});
cutlass::HostTensor<Source, cutlass::layout::RowMajor> source({1, kN});
for (int i = 0; i < kN; ++i) {
source.host_data()[i] = float(i);
}
source.sync_device();
test::core::kernel::convert<Destination, Source, kN><<< grid, block >>>(
reinterpret_cast<cutlass::Array<Destination, kN> *>(destination.device_data()),
reinterpret_cast<cutlass::Array<Source, kN> const *>(source.device_data())
);
destination.sync_host();
for (int i = 0; i < kN; ++i) {
EXPECT_TRUE(float(destination.host_data()[i]) == source.host_data()[i]);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
TEST(NumericConversion, f16_to_f32_rn) {
int const kN = 1;
using Source = cutlass::half_t;
using Destination = float;
dim3 grid(1, 1);
dim3 block(1, 1);
cutlass::HostTensor<float, cutlass::layout::RowMajor> destination({1, kN});
cutlass::HostTensor<cutlass::half_t, cutlass::layout::RowMajor> source({1, kN});
for (int i = 0; i < kN; ++i) {
source.host_data()[i] = Source(i);
}
source.sync_device();
test::core::kernel::convert<Destination, Source, kN><<< grid, block >>>(
reinterpret_cast<cutlass::Array<Destination, kN> *>(destination.device_data()),
reinterpret_cast<cutlass::Array<Source, kN> const *>(source.device_data())
);
destination.sync_host();
for (int i = 0; i < kN; ++i) {
EXPECT_TRUE(float(destination.host_data()[i]) == float(source.host_data()[i]));
}
}
TEST(NumericConversion, f16x8_to_f32x8_rn) {
int const kN = 8;
using Source = cutlass::half_t;
using Destination = float;
dim3 grid(1, 1);
dim3 block(1, 1);
cutlass::HostTensor<float, cutlass::layout::RowMajor> destination({1, kN});
cutlass::HostTensor<cutlass::half_t, cutlass::layout::RowMajor> source({1, kN});
for (int i = 0; i < kN; ++i) {
source.host_data()[i] = float(i);
}
source.sync_device();
test::core::kernel::convert<Destination, Source, kN><<< grid, block >>>(
reinterpret_cast<cutlass::Array<Destination, kN> *>(destination.device_data()),
reinterpret_cast<cutlass::Array<Source, kN> const *>(source.device_data())
);
destination.sync_host();
for (int i = 0; i < kN; ++i) {
EXPECT_TRUE(float(destination.host_data()[i]) == float(source.host_data()[i]));
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////