793 lines
25 KiB
Plaintext
793 lines
25 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017-2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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/*! \file
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\brief Tests cutlass::transform::threadblock::PredicatedTileIterator
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*/
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#include "../../common/cutlass_unit_test.h"
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#include "cutlass/cutlass.h"
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#include "cutlass/transform/pitch_linear_thread_map.h"
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#include "cutlass/transform/threadblock/predicated_tile_iterator.h"
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#include "cutlass/transform/threadblock/predicated_tile_iterator_2dthreadtile.h"
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#include "cutlass/util/tensor_view_io.h"
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#include "cutlass/util/host_tensor.h"
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#include "cutlass/util/reference/host/tensor_fill.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace test {
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namespace transform {
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namespace threadblock {
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namespace kernel {
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/// Copy with an iterator
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template <typename Iterator>
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__global__ void copy(
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typename Iterator::Params dst_params,
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typename Iterator::Element *dst_pointer,
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typename Iterator::Params src_params,
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typename Iterator::Element *src_pointer,
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cutlass::Coord<2> extent) {
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Iterator dst_iterator(dst_params, dst_pointer, extent, threadIdx.x);
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Iterator src_iterator(src_params, src_pointer, extent, threadIdx.x);
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int iterations = (extent[1] + Iterator::Shape::kStrided - 1) / Iterator::Shape::kStrided;
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typename Iterator::Fragment frag;
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for(int i = 0; i < frag.size(); i++)
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frag[i] = 0;
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src_iterator.load(frag);
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dst_iterator.store(frag);
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++dst_iterator;
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++src_iterator;
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for (; iterations > 1; --iterations) {
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src_iterator.load(frag);
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dst_iterator.store(frag);
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++dst_iterator;
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++src_iterator;
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}
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}
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} // namespace kernel
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} // namespace threadblock
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} // namespace transform
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} // namespace test
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined) {
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using Shape = cutlass::layout::PitchLinearShape<64, 4>;
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using Layout = cutlass::layout::PitchLinear;
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using Element = int;
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static int const kThreads = 32;
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using ThreadMap = cutlass::transform::PitchLinearStripminedThreadMap<Shape, kThreads>;
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using Iterator = cutlass::transform::threadblock::PredicatedTileIterator<
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Shape, Element, Layout, 1, ThreadMap
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>;
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cutlass::Coord<2> copy_extent = cutlass::make_Coord(57, 35);
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cutlass::Coord<2> alloc_extent = cutlass::make_Coord(64, 35);
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cutlass::HostTensor<int, Layout> src_tensor(alloc_extent);
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cutlass::HostTensor<int, Layout> dst_tensor(alloc_extent);
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Element oob_value = Element(-1);
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cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
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cutlass::reference::host::BlockFillSequential(src_tensor.host_data(), src_tensor.capacity());
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dst_tensor.sync_device();
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src_tensor.sync_device();
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typename Iterator::Params dst_params(dst_tensor.layout());
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typename Iterator::Params src_params(src_tensor.layout());
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dim3 block(kThreads, 1);
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dim3 grid(1, 1);
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test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
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dst_params,
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dst_tensor.device_data(),
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src_params,
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src_tensor.device_data(),
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copy_extent
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);
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cudaError_t result = cudaGetLastError();
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EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
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dst_tensor.sync_host();
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for (int s = 0; s < alloc_extent[1]; ++s) {
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for (int c = 0; c < alloc_extent[0]; ++c) {
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Element expected = Element(0);
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if (c < copy_extent[0] && s < copy_extent[1]) {
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expected = src_tensor.at({c, s});
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}
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else {
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expected = oob_value;
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}
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Element got = dst_tensor.at({c, s});
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bool equal = (expected == got);
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EXPECT_EQ(expected, got)
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<< "Source:\n" << src_tensor.host_view() << "\n\n"
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<< "Destination:\n" << dst_tensor.host_view() << "\n";
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if (!equal) {
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return;
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}
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}
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_128x4) {
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using Shape = cutlass::layout::PitchLinearShape<128, 4>;
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using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
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using Layout = cutlass::layout::PitchLinear;
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using Element = int8_t;
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static int const kThreads = 32;
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using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
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using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
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Shape, Element, Layout, 1, ThreadMap, false
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>;
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cutlass::Coord<2> copy_extent = cutlass::make_Coord(128, 4);
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cutlass::Coord<2> alloc_extent = cutlass::make_Coord(128, 4);
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cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
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cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
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Element oob_value = Element(-1);
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cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
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cutlass::reference::host::BlockFillSequential(src_tensor.host_data(), src_tensor.capacity());
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dst_tensor.sync_device();
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src_tensor.sync_device();
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typename Iterator::Params dst_params(dst_tensor.layout());
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typename Iterator::Params src_params(src_tensor.layout());
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dim3 block(kThreads, 1);
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dim3 grid(1, 1);
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test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
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dst_params,
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dst_tensor.device_data(),
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src_params,
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src_tensor.device_data(),
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copy_extent
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);
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cudaError_t result = cudaGetLastError();
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EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
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dst_tensor.sync_host();
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for (int s = 0; s < alloc_extent[1]; ++s) {
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for (int c = 0; c < alloc_extent[0]; ++c) {
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Element expected = Element(0);
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if (c < copy_extent[0] && s < copy_extent[1]) {
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expected = src_tensor.at({c, s});
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}
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else {
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expected = oob_value;
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}
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Element got = dst_tensor.at({c, s});
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bool equal = (expected == got);
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EXPECT_EQ(expected, got)
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<< "Source:\n" << src_tensor.host_view() << "\n\n"
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<< "Destination:\n" << dst_tensor.host_view() << "\n";
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if (!equal) {
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return;
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}
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}
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_128x64) {
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using Shape = cutlass::layout::PitchLinearShape<128, 64>;
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using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
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using Layout = cutlass::layout::PitchLinear;
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using Element = int8_t;
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static int const kThreads = 32;
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using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
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using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
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Shape, Element, Layout, 1, ThreadMap
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>;
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cutlass::Coord<2> copy_extent = cutlass::make_Coord(128, 64);
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cutlass::Coord<2> alloc_extent = cutlass::make_Coord(128, 64);
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cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
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cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
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Element oob_value = Element(-1);
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cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
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cutlass::reference::host::BlockFillSequential(src_tensor.host_data(), src_tensor.capacity());
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dst_tensor.sync_device();
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src_tensor.sync_device();
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typename Iterator::Params dst_params(dst_tensor.layout());
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typename Iterator::Params src_params(src_tensor.layout());
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dim3 block(kThreads, 1);
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dim3 grid(1, 1);
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test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
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dst_params,
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dst_tensor.device_data(),
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src_params,
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src_tensor.device_data(),
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copy_extent
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);
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cudaError_t result = cudaGetLastError();
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EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
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dst_tensor.sync_host();
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for (int s = 0; s < alloc_extent[1]; ++s) {
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for (int c = 0; c < alloc_extent[0]; ++c) {
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Element expected = Element(0);
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if (c < copy_extent[0] && s < copy_extent[1]) {
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expected = src_tensor.at({c, s});
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}
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else {
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expected = oob_value;
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}
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Element got = dst_tensor.at({c, s});
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bool equal = (expected == got);
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EXPECT_EQ(expected, got)
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<< "Source:\n" << src_tensor.host_view() << "\n\n"
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<< "Destination:\n" << dst_tensor.host_view() << "\n";
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if (!equal) {
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return;
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}
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}
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////
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TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_64x64) {
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using Shape = cutlass::layout::PitchLinearShape<64, 64>;
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using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
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using Layout = cutlass::layout::PitchLinear;
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using Element = int8_t;
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static int const kThreads = 32;
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using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
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using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
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Shape, Element, Layout, 1, ThreadMap
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>;
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cutlass::Coord<2> copy_extent = cutlass::make_Coord(64, 64);
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cutlass::Coord<2> alloc_extent = cutlass::make_Coord(64, 64);
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cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
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cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
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Element oob_value = Element(-1);
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cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
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cutlass::reference::host::BlockFillSequential(src_tensor.host_data(), src_tensor.capacity());
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dst_tensor.sync_device();
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src_tensor.sync_device();
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typename Iterator::Params dst_params(dst_tensor.layout());
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typename Iterator::Params src_params(src_tensor.layout());
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dim3 block(kThreads, 1);
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dim3 grid(1, 1);
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test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
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dst_params,
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dst_tensor.device_data(),
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src_params,
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src_tensor.device_data(),
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copy_extent
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);
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cudaError_t result = cudaGetLastError();
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EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
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dst_tensor.sync_host();
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for (int s = 0; s < alloc_extent[1]; ++s) {
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for (int c = 0; c < alloc_extent[0]; ++c) {
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Element expected = Element(0);
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if (c < copy_extent[0] && s < copy_extent[1]) {
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expected = src_tensor.at({c, s});
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}
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else {
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expected = oob_value;
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}
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Element got = dst_tensor.at({c, s});
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bool equal = (expected == got);
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EXPECT_EQ(expected, got)
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<< "Source:\n" << src_tensor.host_view() << "\n\n"
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<< "Destination:\n" << dst_tensor.host_view() << "\n";
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if (!equal) {
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return;
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}
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}
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_64x8) {
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using Shape = cutlass::layout::PitchLinearShape<64, 8>;
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using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
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using Layout = cutlass::layout::PitchLinear;
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using Element = int8_t;
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static int const kThreads = 32;
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using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
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using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
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Shape, Element, Layout, 1, ThreadMap
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>;
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cutlass::Coord<2> copy_extent = cutlass::make_Coord(32, 8);
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cutlass::Coord<2> alloc_extent = cutlass::make_Coord(64, 8);
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cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
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cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
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Element oob_value = Element(-1);
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cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
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cutlass::reference::host::BlockFillSequential(src_tensor.host_data(), src_tensor.capacity());
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dst_tensor.sync_device();
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src_tensor.sync_device();
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typename Iterator::Params dst_params(dst_tensor.layout());
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typename Iterator::Params src_params(src_tensor.layout());
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dim3 block(kThreads, 1);
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dim3 grid(1, 1);
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test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
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dst_params,
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dst_tensor.device_data(),
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src_params,
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src_tensor.device_data(),
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copy_extent
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);
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cudaError_t result = cudaGetLastError();
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EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
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dst_tensor.sync_host();
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for (int s = 0; s < alloc_extent[1]; ++s) {
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for (int c = 0; c < alloc_extent[0]; ++c) {
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Element expected = Element(0);
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if (c < copy_extent[0] && s < copy_extent[1]) {
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expected = src_tensor.at({c, s});
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}
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else {
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expected = oob_value;
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}
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Element got = dst_tensor.at({c, s});
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bool equal = (expected == got);
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EXPECT_EQ(expected, got)
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<< "Source:\n" << src_tensor.host_view() << "\n\n"
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<< "Destination:\n" << dst_tensor.host_view() << "\n";
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if (!equal) {
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return;
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}
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}
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_64x32_transpose4x4) {
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using Shape = cutlass::layout::PitchLinearShape<64, 8>;
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using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
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using Layout = cutlass::layout::PitchLinear;
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using Element = int8_t;
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static int const kThreads = 32;
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using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
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using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
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Shape, Element, Layout, 1, ThreadMap, true
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>;
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cutlass::Coord<2> copy_extent = cutlass::make_Coord(64, 32);
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cutlass::Coord<2> alloc_extent = cutlass::make_Coord(64, 32);
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cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
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cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
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Element oob_value = Element(-1);
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uint64_t seed = 7;
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cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
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cutlass::reference::host::TensorFillRandomUniform(src_tensor.host_view(), seed, 8, -8, 0);
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dst_tensor.sync_device();
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src_tensor.sync_device();
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typename Iterator::Params dst_params(dst_tensor.layout());
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typename Iterator::Params src_params(src_tensor.layout());
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dim3 block(kThreads, 1);
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dim3 grid(1, 1);
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test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
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dst_params,
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dst_tensor.device_data(),
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src_params,
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src_tensor.device_data(),
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copy_extent
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);
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cudaError_t result = cudaGetLastError();
|
|
EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
|
|
|
|
dst_tensor.sync_host();
|
|
|
|
for (int s = 0; s < alloc_extent[1]/4; ++s) {
|
|
for (int c = 0; c < alloc_extent[0]/4; ++c) {
|
|
for (int s1 = 0; s1 < 4; s1++){
|
|
for(int c1 = 0; c1 < 4; c1++){
|
|
Element expected = Element(0);
|
|
|
|
int l_c = c * 4 + c1;
|
|
int l_s = s * 4 + s1;
|
|
|
|
int l_tc = c * 4 + s1;
|
|
int l_ts = s * 4 + c1;
|
|
|
|
if (l_c < copy_extent[0] && l_s < copy_extent[1]) {
|
|
expected = src_tensor.at({l_c, l_s});
|
|
}
|
|
else {
|
|
expected = oob_value;
|
|
}
|
|
|
|
Element got = dst_tensor.at({l_tc, l_ts});
|
|
bool equal = (expected == got);
|
|
|
|
EXPECT_EQ(expected, got)
|
|
<< "Source:\n" << src_tensor.host_view() << "\n\n"
|
|
<< "Destination:\n" << dst_tensor.host_view() << "\n";
|
|
|
|
if (!equal) {
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_64x29_transpose4x4) {
|
|
|
|
using Shape = cutlass::layout::PitchLinearShape<64, 8>;
|
|
using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
|
|
using Layout = cutlass::layout::PitchLinear;
|
|
using Element = int8_t;
|
|
static int const kThreads = 32;
|
|
|
|
using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
|
|
|
|
using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
|
|
Shape, Element, Layout, 1, ThreadMap, true
|
|
>;
|
|
|
|
cutlass::Coord<2> copy_extent = cutlass::make_Coord(64, 29);
|
|
cutlass::Coord<2> alloc_extent = cutlass::make_Coord(64, 29);
|
|
|
|
cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
|
|
cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
|
|
|
|
Element oob_value = Element(-1);
|
|
uint64_t seed = 7;
|
|
cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
|
|
cutlass::reference::host::TensorFillRandomUniform(src_tensor.host_view(), seed, 8, -8, 0);
|
|
|
|
dst_tensor.sync_device();
|
|
src_tensor.sync_device();
|
|
|
|
typename Iterator::Params dst_params(dst_tensor.layout());
|
|
typename Iterator::Params src_params(src_tensor.layout());
|
|
|
|
dim3 block(kThreads, 1);
|
|
dim3 grid(1, 1);
|
|
|
|
test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
|
|
dst_params,
|
|
dst_tensor.device_data(),
|
|
src_params,
|
|
src_tensor.device_data(),
|
|
copy_extent
|
|
);
|
|
|
|
cudaError_t result = cudaGetLastError();
|
|
EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
|
|
|
|
dst_tensor.sync_host();
|
|
|
|
for (int s = 0; s < alloc_extent[1]/4; ++s) {
|
|
for (int c = 0; c < alloc_extent[0]/4; ++c) {
|
|
for (int s1 = 0; s1 < 4; s1++){
|
|
for(int c1 = 0; c1 < 4; c1++){
|
|
Element expected = Element(0);
|
|
|
|
int l_c = c * 4 + c1;
|
|
int l_s = s * 4 + s1;
|
|
|
|
int l_tc = c * 4 + s1;
|
|
int l_ts = s * 4 + c1;
|
|
|
|
if (l_c < copy_extent[0] && l_s < copy_extent[1]) {
|
|
expected = src_tensor.at({l_c, l_s});
|
|
}
|
|
else {
|
|
expected = oob_value;
|
|
}
|
|
|
|
Element got = dst_tensor.at({l_tc, l_ts});
|
|
bool equal = (expected == got);
|
|
|
|
EXPECT_EQ(expected, got)
|
|
<< "Source:\n" << src_tensor.host_view() << "\n\n"
|
|
<< "Destination:\n" << dst_tensor.host_view() << "\n";
|
|
|
|
if (!equal) {
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_120x4_transpose4x4) {
|
|
|
|
using Shape = cutlass::layout::PitchLinearShape<128, 4>;
|
|
using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
|
|
using Layout = cutlass::layout::PitchLinear;
|
|
using Element = int8_t;
|
|
static int const kThreads = 32;
|
|
|
|
using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
|
|
|
|
using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
|
|
Shape, Element, Layout, 1, ThreadMap, true
|
|
>;
|
|
|
|
cutlass::Coord<2> copy_extent = cutlass::make_Coord(120, 4);
|
|
cutlass::Coord<2> alloc_extent = cutlass::make_Coord(120, 4);
|
|
|
|
cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
|
|
cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
|
|
|
|
Element oob_value = Element(-1);
|
|
uint64_t seed = 7;
|
|
cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
|
|
cutlass::reference::host::TensorFillRandomUniform(src_tensor.host_view(), seed, 8, -8, 0);
|
|
|
|
dst_tensor.sync_device();
|
|
src_tensor.sync_device();
|
|
|
|
typename Iterator::Params dst_params(dst_tensor.layout());
|
|
typename Iterator::Params src_params(src_tensor.layout());
|
|
|
|
dim3 block(kThreads, 1);
|
|
dim3 grid(1, 1);
|
|
|
|
test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
|
|
dst_params,
|
|
dst_tensor.device_data(),
|
|
src_params,
|
|
src_tensor.device_data(),
|
|
copy_extent
|
|
);
|
|
|
|
cudaError_t result = cudaGetLastError();
|
|
EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
|
|
|
|
dst_tensor.sync_host();
|
|
|
|
for (int s = 0; s < alloc_extent[1]/4; ++s) {
|
|
for (int c = 0; c < alloc_extent[0]/4; ++c) {
|
|
for (int s1 = 0; s1 < 4; s1++){
|
|
for(int c1 = 0; c1 < 4; c1++){
|
|
Element expected = Element(0);
|
|
|
|
int l_c = c * 4 + c1;
|
|
int l_s = s * 4 + s1;
|
|
|
|
int l_tc = c * 4 + s1;
|
|
int l_ts = s * 4 + c1;
|
|
|
|
if (l_c < copy_extent[0] && l_s < copy_extent[1]) {
|
|
expected = src_tensor.at({l_c, l_s});
|
|
}
|
|
else {
|
|
expected = oob_value;
|
|
}
|
|
|
|
Element got = dst_tensor.at({l_tc, l_ts});
|
|
bool equal = (expected == got);
|
|
|
|
EXPECT_EQ(expected, got)
|
|
<< "Source:\n" << src_tensor.host_view() << "\n\n"
|
|
<< "Destination:\n" << dst_tensor.host_view() << "\n";
|
|
|
|
if (!equal) {
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(Transform_threadblock_PredicatedTileIterator, PitchLinear_Stripmined_2dtile_48x29_transpose4x4) {
|
|
|
|
using Shape = cutlass::layout::PitchLinearShape<64, 8>;
|
|
using ThreadTileShape = cutlass::layout::PitchLinearShape<4, 4>;
|
|
using Layout = cutlass::layout::PitchLinear;
|
|
using Element = int8_t;
|
|
static int const kThreads = 32;
|
|
|
|
using ThreadMap = cutlass::transform::PitchLinear2DThreadTileStripminedThreadMap<Shape, kThreads, ThreadTileShape>;
|
|
|
|
using Iterator = cutlass::transform::threadblock::PredicatedTileIterator2dThreadTile<
|
|
Shape, Element, Layout, 1, ThreadMap, true
|
|
>;
|
|
|
|
cutlass::Coord<2> copy_extent = cutlass::make_Coord(48, 29);
|
|
cutlass::Coord<2> alloc_extent = cutlass::make_Coord(48, 29);
|
|
|
|
cutlass::HostTensor<int8_t, Layout> src_tensor(alloc_extent);
|
|
cutlass::HostTensor<int8_t, Layout> dst_tensor(alloc_extent);
|
|
|
|
Element oob_value = Element(-1);
|
|
uint64_t seed = 7;
|
|
cutlass::reference::host::TensorFill(dst_tensor.host_view(), oob_value);
|
|
cutlass::reference::host::TensorFillRandomUniform(src_tensor.host_view(), seed, 8, -8, 0);
|
|
|
|
dst_tensor.sync_device();
|
|
src_tensor.sync_device();
|
|
|
|
typename Iterator::Params dst_params(dst_tensor.layout());
|
|
typename Iterator::Params src_params(src_tensor.layout());
|
|
|
|
dim3 block(kThreads, 1);
|
|
dim3 grid(1, 1);
|
|
|
|
test::transform::threadblock::kernel::copy<Iterator><<< grid, block >>>(
|
|
dst_params,
|
|
dst_tensor.device_data(),
|
|
src_params,
|
|
src_tensor.device_data(),
|
|
copy_extent
|
|
);
|
|
|
|
cudaError_t result = cudaGetLastError();
|
|
EXPECT_EQ(result, cudaSuccess) << " - CUDA error: " << cudaGetErrorString(result);
|
|
|
|
dst_tensor.sync_host();
|
|
|
|
for (int s = 0; s < alloc_extent[1]/4; ++s) {
|
|
for (int c = 0; c < alloc_extent[0]/4; ++c) {
|
|
for (int s1 = 0; s1 < 4; s1++){
|
|
for(int c1 = 0; c1 < 4; c1++){
|
|
Element expected = Element(0);
|
|
|
|
int l_c = c * 4 + c1;
|
|
int l_s = s * 4 + s1;
|
|
|
|
int l_tc = c * 4 + s1;
|
|
int l_ts = s * 4 + c1;
|
|
|
|
if (l_c < copy_extent[0] && l_s < copy_extent[1]) {
|
|
expected = src_tensor.at({l_c, l_s});
|
|
}
|
|
else {
|
|
expected = oob_value;
|
|
}
|
|
|
|
Element got = dst_tensor.at({l_tc, l_ts});
|
|
bool equal = (expected == got);
|
|
|
|
EXPECT_EQ(expected, got)
|
|
<< "Source:\n" << src_tensor.host_view() << "\n\n"
|
|
<< "Destination:\n" << dst_tensor.host_view() << "\n";
|
|
if (!equal) {
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|