mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-03-25 09:37:42 +00:00
[CK-tile] add more tests for batched transpose testing the rectangular block tile sizes (#2634)
* add failing tests * swap out and reference * add constraint assert to transpose input distribution * test both pipelines with rectangular block tile * print mismatched indices * add a smaller failing test for old pipeline * print grid and block * fill output before operating on it * swap m/n tile sizes and make one test pass * add device syncs * add one more flipped test case * flip block tile at host arg init * fix tiles for lds pipeline * clang-format * rename tests * roll back error check * remove device syncs * reduce large test case's size
This commit is contained in:
@@ -49,9 +49,11 @@ struct BatchedTransposeKernel
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CK_TILE_HOST static constexpr auto GridSize(const Hargs& host_args)
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{
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size_t grid_size_x = (host_args.height + host_args.dim_block_h - 1) / host_args.dim_block_h;
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size_t grid_size_y = (host_args.width + host_args.dim_block_w - 1) / host_args.dim_block_w;
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size_t grid_size_z = host_args.batch;
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const size_t grid_size_x =
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ck_tile::integer_divide_ceil(host_args.height, host_args.dim_block_h);
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const size_t grid_size_y =
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ck_tile::integer_divide_ceil(host_args.width, host_args.dim_block_w);
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const size_t grid_size_z = host_args.batch;
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return dim3(grid_size_x, grid_size_y, grid_size_z);
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}
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@@ -71,41 +73,43 @@ struct BatchedTransposeKernel
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CK_TILE_DEVICE void operator()(Kargs kargs) const
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{
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static constexpr ck_tile::index_t kMPerBlock = Problem::kMPerBlock;
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static constexpr ck_tile::index_t kNPerBlock = Problem::kNPerBlock;
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static constexpr bool kPadM = Problem::kPadM;
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static constexpr bool kPadN = Problem::kPadN;
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static constexpr ck_tile::index_t VectorSizeInput = Problem::VectorSizeInput;
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static constexpr ck_tile::index_t VectorSizeOutput = Problem::VectorSizeOutput;
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static constexpr ck_tile::index_t kMPerBlock = Problem::kMPerBlock;
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static constexpr ck_tile::index_t kNPerBlock = Problem::kNPerBlock;
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static constexpr bool kPadM = Problem::kPadM;
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static constexpr bool kPadN = Problem::kPadN;
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static constexpr ck_tile::index_t VectorSizeInput = Problem::VectorSizeInput;
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static constexpr ck_tile::index_t VectorStrideInput = 1;
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static constexpr ck_tile::index_t VectorSizeOutput = Problem::VectorSizeOutput;
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static constexpr ck_tile::index_t VectorStrideOutput = 1;
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const auto iM = __builtin_amdgcn_readfirstlane(blockIdx.x * kMPerBlock);
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const auto iN = __builtin_amdgcn_readfirstlane(blockIdx.y * kNPerBlock);
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const auto iDim = blockIdx.z;
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const auto iM = __builtin_amdgcn_readfirstlane(blockIdx.x * kMPerBlock);
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const auto iN = __builtin_amdgcn_readfirstlane(blockIdx.y * kNPerBlock);
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const auto offset = __builtin_amdgcn_readfirstlane(blockIdx.z * kargs.height * kargs.width);
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const auto x_m_n = [&]() {
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const auto x_dram_naive = make_naive_tensor_view<address_space_enum::global>(
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static_cast<const Type*>(kargs.p_input) + iDim * kargs.dim_stride,
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static_cast<const Type*>(kargs.p_input) + offset,
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make_tuple(kargs.height, kargs.width),
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make_tuple(kargs.width, 1),
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number<VectorSizeInput>{},
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number<1>{});
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number<VectorStrideInput>{});
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return pad_tensor_view(x_dram_naive,
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make_tuple(number<kMPerBlock>{}, number<kNPerBlock>{}),
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sequence<kPadN, kPadM>{});
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sequence<kPadM, kPadN>{});
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}();
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const auto y_n_m = [&]() {
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const auto y_dram_naive = make_naive_tensor_view<address_space_enum::global>(
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static_cast<Type*>(kargs.p_output) + iDim * kargs.dim_stride,
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static_cast<Type*>(kargs.p_output) + offset,
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make_tuple(kargs.width, kargs.height),
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make_tuple(kargs.height, 1),
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number<VectorSizeOutput>{},
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number<1>{});
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number<VectorStrideOutput>{});
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return pad_tensor_view(y_dram_naive,
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make_tuple(number<kNPerBlock>{}, number<kMPerBlock>{}),
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sequence<kPadM, kPadN>{});
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sequence<kPadN, kPadM>{});
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}();
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auto x_block_window = make_tile_window(
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@@ -15,15 +15,15 @@ struct BatchedTransposeCommonPolicy
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template <typename Problem>
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CK_TILE_DEVICE static constexpr auto MakeInputDistribution()
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{
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constexpr index_t BlockSize = Problem::kBlockSize;
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constexpr index_t LeadDimPerBlock = Problem::kMPerBlock;
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constexpr index_t SecondDimPerBlock = Problem::kNPerBlock;
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constexpr index_t kBlockSize = Problem::kBlockSize;
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constexpr index_t kLeadDimPerBlock = Problem::kNPerBlock;
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constexpr index_t kSecondDimPerBlock = Problem::kMPerBlock;
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constexpr index_t kVectorSize = Problem::VectorSizeOutput;
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using TileEncodingPattern = TileDistributionEncodingPattern2D<BlockSize,
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SecondDimPerBlock,
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LeadDimPerBlock,
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constexpr index_t kVectorSize = Problem::VectorSizeInput;
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static_assert((kLeadDimPerBlock * kVectorSize) % kBlockSize == 0, "");
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using TileEncodingPattern = TileDistributionEncodingPattern2D<kBlockSize,
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kSecondDimPerBlock,
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kLeadDimPerBlock,
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kVectorSize,
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TileAccessPattern>;
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return TileEncodingPattern::Make2DStaticTileDistribution();
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@@ -18,19 +18,19 @@ struct BatchedTransposeLdsProblem
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{
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using DataType = remove_cvref_t<DataType_>;
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static constexpr index_t kRowWarps_ = NumWarps::at(number<1>{});
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static constexpr index_t kColWarps_ = NumWarps::at(number<0>{});
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static constexpr index_t kRowWarps_ = NumWarps::at(number<0>{});
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static constexpr index_t kColWarps_ = NumWarps::at(number<1>{});
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static constexpr index_t kBlockSize_ = get_warp_size() * kRowWarps_ * kColWarps_;
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static constexpr index_t kRowPerBlock_ = BlockTile::at(number<1>{});
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static constexpr index_t kColPerBlock_ = BlockTile::at(number<0>{});
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static constexpr index_t kRowPerBlock_ = BlockTile::at(number<0>{});
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static constexpr index_t kColPerBlock_ = BlockTile::at(number<1>{});
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static constexpr index_t kBlockSize = kBlockSize_;
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// warps per block
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static constexpr index_t kLeadNumWarps = kRowWarps_;
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static constexpr index_t kSecondNumWarps = kColWarps_;
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static constexpr index_t kLeadNumWarps = kColWarps_;
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static constexpr index_t kSecondNumWarps = kRowWarps_;
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static constexpr index_t kLeadSizePerBlock = kRowPerBlock_;
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static constexpr index_t kSecondSizePerBlock = kColPerBlock_;
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static constexpr index_t kLeadSizePerBlock = kColPerBlock_;
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static constexpr index_t kSecondSizePerBlock = kRowPerBlock_;
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static constexpr index_t kQuadrantLeadDim = LaneGroupTransposeTraits<DataType>::kleadDim;
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static constexpr index_t kQuadrantSecondDim = LaneGroupTransposeTraits<DataType>::ksecondDim;
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@@ -60,8 +60,8 @@ struct BatchedTransposeLdsProblem
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static constexpr bool kPadM = kPadM_;
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static constexpr bool kPadN = kPadN_;
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static constexpr auto kMPerBlock = kLeadSizePerBlock;
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static constexpr auto kNPerBlock = kSecondSizePerBlock;
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static constexpr auto kMPerBlock = kSecondSizePerBlock;
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static constexpr auto kNPerBlock = kLeadSizePerBlock;
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// 128-bit is the max single-instruction bandwidth for load/store
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static constexpr index_t MaxLoadStoreSize = 16;
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@@ -19,8 +19,8 @@ struct BatchedTransposePolicy : public BatchedTransposeCommonPolicy
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constexpr index_t VecLoadSize = Problem::VectorSizeOutput;
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using TileEncodingPattern = TileDistributionEncodingPattern2D<BlockSize,
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NPerBlock,
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MPerBlock,
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NPerBlock,
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VecLoadSize,
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TileAccessPattern>;
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return TileEncodingPattern::MakeShuffled2DStaticTileDistribution();
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@@ -95,10 +95,12 @@ class TestCkTileBatchedTranspose // N C H W layout_in==
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ck_tile::HostTensor<DataType> y_ref(Y_dim, Y_stride);
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ck_tile::FillUniformDistribution<DataType>{-.5f, .5f}(x_host);
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ck_tile::FillConstant<DataType>{-37}(y_host);
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ck_tile::DeviceMem x_dev(x_host.get_element_space_size_in_bytes());
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ck_tile::DeviceMem y_dev(y_host.get_element_space_size_in_bytes());
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x_dev.ToDevice(x_host.data());
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y_dev.ToDevice(y_host.data());
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using Kernel = typename Config::Kernel;
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@@ -131,8 +133,8 @@ class TestCkTileBatchedTranspose // N C H W layout_in==
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height,
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width,
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height * width,
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Config::BlockTile::at(1),
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Config::BlockTile::at(0)};
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Config::BlockTile::at(0),
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Config::BlockTile::at(1)};
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auto kargs = Kernel::MakeKargs(host_args);
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auto sc = ck_tile::stream_config{};
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@@ -140,15 +142,24 @@ class TestCkTileBatchedTranspose // N C H W layout_in==
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constexpr dim3 block_size = Kernel::BlockSize();
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ck_tile::launch_kernel(
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sc, ck_tile::make_kernel<block_size.x, 1>(Kernel{}, grid_size, block_size, 0, kargs));
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y_dev.FromDevice(y_host.data());
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ck_tile::reference_batched_transpose<DataType>(x_host, y_ref, layout_in, layout_out);
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std::ostringstream message;
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message << "N=" << N << " C=" << C << " H=" << H << " W=" << W << " layout_in=" << layout_in
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<< " layout_out=" << layout_out << " device_name=" << device_name;
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<< " layout_out=" << layout_out << " grid_size={" << grid_size.x << ", "
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<< grid_size.y << ", " << grid_size.z << "} block_size=" << block_size.x
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<< " device_name=" << device_name;
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// NB: order of output and reference matters
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bool pass = ck_tile::check_err(
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y_ref, y_host, message.str(), /* rtol */ 0, /* atol */ 0, /* allow inf */ false);
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/* out */ y_host,
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/* ref */ y_ref,
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message.str(),
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/* rtol */ 0,
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/* atol */ 0,
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/* allow inf */ false);
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EXPECT_TRUE(pass);
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}
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@@ -160,14 +171,16 @@ static const auto kTestingValues = ::testing::Values(
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// N C H W layout_in==NCHW
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std::tuple{1, 32, 1, 32, true},
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std::tuple{1, 64, 1, 64, true},
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std::tuple{1, 32, 1, 64, true},
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std::tuple{1, 64, 1, 32, true},
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std::tuple{2, 12, 1, 32, false},
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std::tuple{3, 1334, 1, 37, false},
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std::tuple{4, 27, 1, 32, true},
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std::tuple{5, 1234, 1, 12, true},
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std::tuple{1, 1, 1, 1, true},
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std::tuple{1, 1, 1, 1, false},
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std::tuple{128, 1024, 64, 64, true},
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std::tuple{128, 1024, 64, 64, false},
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std::tuple{17, 1024, 64, 64, true},
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std::tuple{17, 1024, 64, 64, false},
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std::tuple{16, 64, 32, 128, true},
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std::tuple{16, 64, 128, 32, false},
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std::tuple{1, 2048, 1, 1, true},
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@@ -239,6 +252,60 @@ class CaseHalfPadMultiWarpLoadTranspose
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{
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};
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class CaseHalfPadMultiWarp128MNLoadTranspose
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: public TestCkTileBatchedTranspose<PipelineConfig<ck_tile::half_t,
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PipelineTag::LDSLoadTranspose,
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128,
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128,
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2,
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2,
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false,
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false>>
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{
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};
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class CaseHalfPadMultiWarp128MN
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: public TestCkTileBatchedTranspose<
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PipelineConfig<ck_tile::half_t, PipelineTag::Universal, 128, 128, 2, 2, false, false>>
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{
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};
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class CaseHalfPadRectTile1
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: public TestCkTileBatchedTranspose<
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PipelineConfig<ck_tile::half_t, PipelineTag::Universal, 32, 64, 1, 1, false, false>>
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{
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};
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class CaseHalfPadRectTile2
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: public TestCkTileBatchedTranspose<
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PipelineConfig<ck_tile::half_t, PipelineTag::Universal, 64, 32, 1, 1, false, false>>
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{
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};
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class CaseHalfPadRectTile1LoadTranspose
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: public TestCkTileBatchedTranspose<PipelineConfig<ck_tile::half_t,
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PipelineTag::LDSLoadTranspose,
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32,
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64,
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1,
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1,
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false,
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false>>
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{
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};
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class CaseHalfPadRectTile2LoadTranspose
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: public TestCkTileBatchedTranspose<PipelineConfig<ck_tile::half_t,
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PipelineTag::LDSLoadTranspose,
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64,
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32,
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1,
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1,
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false,
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false>>
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{
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};
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TEST_P(CaseHalf, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseByte, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseWord, TestCorrectness) { this->Run(GetParam()); }
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@@ -248,6 +315,12 @@ TEST_P(CaseHalfPad, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadLoadTranspose, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadMultiWarp, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadMultiWarpLoadTranspose, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadMultiWarp128MN, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadMultiWarp128MNLoadTranspose, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadRectTile1, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadRectTile1LoadTranspose, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadRectTile2, TestCorrectness) { this->Run(GetParam()); }
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TEST_P(CaseHalfPadRectTile2LoadTranspose, TestCorrectness) { this->Run(GetParam()); }
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// clang-format off
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalf, kTestingValues);
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@@ -259,4 +332,11 @@ INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPad, kTestingV
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadLoadTranspose, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadMultiWarp, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadMultiWarpLoadTranspose, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadMultiWarp128MN, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadMultiWarp128MNLoadTranspose, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadRectTile1, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadRectTile1LoadTranspose, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadRectTile2, kTestingValues);
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INSTANTIATE_TEST_SUITE_P(TestCkTileBatchedTransposeSuite, CaseHalfPadRectTile2LoadTranspose, kTestingValues);
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// clang-format on
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