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All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, are permitted * provided that the following conditions are met: * * Redistributions of source code must retain the above copyright notice, this list of * conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright notice, this list of * conditions and the following disclaimer in the documentation and/or other materials * provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used * to endorse or promote products derived from this software without specific prior written * permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ /*! \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 __global__ void convert( cutlass::Array *destination, cutlass::Array const *source) { cutlass::NumericArrayConverter 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 destination({1, kN}); cutlass::HostTensor source({1, kN}); for (int i = 0; i < kN; ++i) { source.host_data()[i] = float(i); } source.sync_device(); test::core::kernel::convert<<< grid, block >>>( reinterpret_cast *>(destination.device_data()), reinterpret_cast 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({1, kN}); cutlass::HostTensor source({1, kN}); for (int i = 0; i < kN; ++i) { source.host_data()[i] = float(i); } source.sync_device(); test::core::kernel::convert<<< grid, block >>>( reinterpret_cast *>(destination.device_data()), reinterpret_cast 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 destination({1, kN}); cutlass::HostTensor source({1, kN}); for (int i = 0; i < kN; ++i) { source.host_data()[i] = Source(i); } source.sync_device(); test::core::kernel::convert<<< grid, block >>>( reinterpret_cast *>(destination.device_data()), reinterpret_cast 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 destination({1, kN}); cutlass::HostTensor source({1, kN}); for (int i = 0; i < kN; ++i) { source.host_data()[i] = float(i); } source.sync_device(); test::core::kernel::convert<<< grid, block >>>( reinterpret_cast *>(destination.device_data()), reinterpret_cast 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])); } } /////////////////////////////////////////////////////////////////////////////////////////////////