Files
composable_kernel/experimental/builder/test/conv/ck/test_conv_traits.cpp
kabrahamAMD 5e06874aae [rocm-libraries] ROCm/rocm-libraries#4582 (commit 990a00d)
[CK_Builder] added bwd data kernels to builder factory
 (#4582)

This PR adds bwd data wmma and xdl kernels to the ck builder, their
instance and conv traits as well as tests for the above.
2026-02-27 03:06:29 +00:00

1830 lines
104 KiB
C++

// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <gtest/gtest.h>
#include <gmock/gmock.h>
#include <concepts>
#include <ck/tensor_operation/gpu/element/element_wise_operation.hpp>
#include <ck_tile/builder/reflect/instance_to_conv_traits.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_fwd_multiple_abd_xdl_cshuffle_v3.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_fwd_multiple_abd_xdl_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_fwd_multiple_d_wmma_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_fwd_multiple_d_xdl_large_tensor_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_xdl_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_multiple_d_xdl_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_multiple_d_wmma_cshuffle_v3.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_two_stage_xdl_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_two_stage_wmma_cshuffle_v3.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_wmma_cshuffle_v3.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_weight_wmma_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_data_multiple_d_xdl_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_data_multiple_d_wmma_cshuffle.hpp>
#include <ck_tile/builder/reflect/instance_traits_device_grouped_conv_bwd_data_multiple_d_wmma_cshuffle_v3.hpp>
namespace {
using ck_tile::builder::ConvDirection;
using ck_tile::builder::DataType;
using ck_tile::builder::ElementwiseOperation;
using ck_tile::builder::PipelineScheduler;
using ck_tile::builder::PipelineVersion;
using ck_tile::builder::TensorLayout;
using ::testing::ElementsAre;
// Test fixture for ConvTraits tests
class ConvTraitsTest : public ::testing::Test
{
};
// Test ConvTraits with DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
TEST_F(ConvTraitsTest, ConvBwdDataMultipleDCshuffleWmmaTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::half_t, // OutDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::Tuple<>, // DsDataType
float, // OutComputeType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::
Default, // ConvBackwardDataSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerWMMA
32, // NPerWMMA
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMRepeatPerWavePerShuffle
1, // CShuffleNRepeatPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
2, // NumGemmKPrefetchStage
ck::LoopScheduler::Default, // BlkGemmPipeSched
ck::PipelineVersion::v1>; // PipelineVerison
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_DATA);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP32);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
EXPECT_EQ(traits.num_gemm_k_prefetch_stage, 2);
// Verify pipeline configuration
}
// Test ConvTraits with DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle_V3
TEST_F(ConvTraitsTest, ConvBwdDataMultipleDCshuffleWmmaV3TraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffleV3<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::half_t, // OutDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::Tuple<>, // DsDataType
float, // OutComputeType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::
Default, // ConvBackwardDataSpecialization
false, // DoPadGemmM
false, // DoPadGemmN
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // AK1
8, // BK1
32, // MPerWMMA
32, // NPerWMMA
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMRepeatPerWavePerShuffle
1, // CShuffleNRepeatPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
ck::Sequence<8, 8, 8>, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
1, // MaxTransposeTransferSrcScalarPerVector
1>; // MaxTransposeTransferDstScalarPerVector
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_DATA);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP32);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
EXPECT_FALSE(traits.do_pad_gemm_n.value());
EXPECT_FALSE(traits.do_pad_gemm_m.value());
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
EXPECT_EQ(traits.max_transpose_transfer_src_scalar_per_vector, 1);
EXPECT_EQ(traits.max_transpose_transfer_dst_scalar_per_vector, 1);
// Verify pipeline configuration
}
// Test ConvTraits with DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle
TEST_F(ConvTraitsTest, ConvBwdDataMultipleDCshuffleXDLTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::half_t, // OutDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::Tuple<>, // DsDataType
float, // OutComputeType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::
Default, // ConvBackwardDataSpecialization
false, // DoPadGemmM
false, // DoPadGemmN
1, // num_gemm_k_prefetch_stage
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // AK1
8, // BK1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::LoopScheduler::Default, // BlkGemmPipeSched
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
1, // MaxTransposeTransferSrcScalarPerVector
1>; // MaxTransposeTransferDstScalarPerVector
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_DATA);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP32);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
EXPECT_EQ(traits.num_gemm_k_prefetch_stage, 1);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
EXPECT_FALSE(traits.do_pad_gemm_n.value());
EXPECT_FALSE(traits.do_pad_gemm_m.value());
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
EXPECT_EQ(traits.max_transpose_transfer_src_scalar_per_vector, 1);
EXPECT_EQ(traits.max_transpose_transfer_dst_scalar_per_vector, 1);
}
// Test ConvTraits with DeviceGroupedConvBwdWeight_Wmma_CShuffle
TEST_F(ConvTraitsTest, ConvBwdWeightCshuffleWmmaTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance = ck::tensor_operation::device::DeviceGroupedConvBwdWeight_Wmma_CShuffle<
3, // NDimSpatial
ck::tensor_layout::convolution::GNDHWC, // InLayout
ck::tensor_layout::convolution::GKZYXC, // WeiLayout
ck::tensor_layout::convolution::GNDHWK, // OutLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerWmma
32, // NPerWmma
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
1, // NummGemmKPrefetchStage
ck::LoopScheduler::Default, // BlkGemmPipeSched
ck::PipelineVersion::v1, // BlkGemmPipelineVer
false>; // BComputeDataType
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 3);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNDHWC, TensorLayout::GKZYXC, TensorLayout::GNDHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
}
// Test ConvTraits with DeviceGroupedConvBwdWeight_Xdl_CShuffle_V3
TEST_F(ConvTraitsTest, ConvBwdWeightCshuffleWmmaV3TraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance = ck::tensor_operation::device::DeviceGroupedConvBwdWeight_Wmma_CShuffleV3<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerWmma
32, // NPerWmma
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
1, // MaxTransposeTransferSrcScalarPerVector
1>; // MaxTransposeTransferDstScalarPerVector>
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
EXPECT_EQ(traits.max_transpose_transfer_src_scalar_per_vector, 1);
EXPECT_EQ(traits.max_transpose_transfer_dst_scalar_per_vector, 1);
// Verify pipeline configuration
}
// Test ConvTraits with DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffle_V3
TEST_F(ConvTraitsTest, ConvBwdWeightMultipleDCshuffleWmmaV3TraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdWeightMultipleD_Wmma_CShuffleV3<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::Tuple<>, // DsLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::Tuple<>, // DsDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerWmma
32, // NPerWmma
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
ck::half_t, // AComputeDataType
ck::half_t>; // BComputeDataType
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
}
// Test ConvTraits with DeviceGroupedConvBwdWeight_two_stage_Xdl_CShuffleV3
TEST_F(ConvTraitsTest, ConvBwdWeightTwoStageWmmaCshuffleTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdWeightTwoStage_Wmma_CShuffleV3<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // AK1
32, // MPerWMMA
32, // NPerXDL
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
4, // NumGroupsToMerge
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
1, // MaxTransposeTransferSrcScalarPerVector
1>; // MaxTransposeTransferDstScalarPerVector>
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
EXPECT_EQ(traits.pipeline_version, PipelineVersion::V1);
EXPECT_EQ(traits.max_transpose_transfer_src_scalar_per_vector, 1);
EXPECT_EQ(traits.max_transpose_transfer_dst_scalar_per_vector, 1);
}
// Test ConvTraits with DeviceGroupedConvBwdWeight_two_stage_Xdl_CShuffleV3
TEST_F(ConvTraitsTest, ConvBwdWeightTwoStageXdlCshuffleTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdWeightTwoStage_Xdl_CShuffle<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
4, // NumGroupsToMerge
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
1, // MaxTransposeTransferSrcScalarPerVector
1>; // MaxTransposeTransferDstScalarPerVector>
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
EXPECT_EQ(traits.pipeline_version, PipelineVersion::V1);
EXPECT_EQ(traits.max_transpose_transfer_src_scalar_per_vector, 1);
EXPECT_EQ(traits.max_transpose_transfer_dst_scalar_per_vector, 1);
}
// Test ConvTraits with DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle
TEST_F(ConvTraitsTest, ConvBwdWeightMultipleDCshuffleXDLTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::Tuple<>, // DsLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::Tuple<>, // DsDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::half_t, // AComputeDataType
ck::half_t>; // BComputeDataType
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
}
// Test ConvTraits with DeviceGroupedConvBwdWeight_Xdl_CShuffleV3
TEST_F(ConvTraitsTest, ConvBwdWeightXdlCshuffleV3TraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance = ck::tensor_operation::device::DeviceGroupedConvBwdWeight_Xdl_CShuffleV3<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
false, // DirectLoad
1>; // NumGroupsToMerge
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
EXPECT_EQ(traits.pipeline_version, PipelineVersion::V1);
}
// Test ConvTraits with DeviceGroupedConvBwdWeight_Xdl_CShuffle
TEST_F(ConvTraitsTest, ConvBwdWeightXdlCshuffleTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance = ck::tensor_operation::device::DeviceGroupedConvBwdWeight_Xdl_CShuffle<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // InLayout
ck::tensor_layout::convolution::GKYXC, // WeiLayout
ck::tensor_layout::convolution::GNHWK, // OutLayout
ck::half_t, // InDataType
ck::half_t, // WeiDataType
ck::half_t, // OutDataType
float, // AccDataType
ck::tensor_operation::element_wise::PassThrough, // InElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // WeiElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // OutElementwiseOperation
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::
Default, // ConvBackwardWeightSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // K0PerBlock
8, // K1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_K1
1, // ABlockLdsAddExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder_
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder_
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_K1
1, // BBlockLdsAddExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock_
8, // CDEBlockTransferScalarPerVector_NPerBlock_
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
1, // MaxTransposeTransferSrcScalarPerVector
1>; // MaxTransposeTransferDstScalarPerVector>
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::BACKWARD_WEIGHT);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::DEFAULT);
EXPECT_EQ(traits.pipeline_version, PipelineVersion::V1);
EXPECT_EQ(traits.max_transpose_transfer_src_scalar_per_vector, 1);
EXPECT_EQ(traits.max_transpose_transfer_dst_scalar_per_vector, 1);
}
// test conv traits device_grouped_conv_fwd_multiple_d_wmma_cshuffle.hpp
TEST_F(ConvTraitsTest, ConvFwdTraitsMultipleDCshuffleWmmaExtraction)
{
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleD_Wmma_CShuffle<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // ALayout
ck::tensor_layout::convolution::GKYXC, // BLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWK, // ELayout
ck::half_t, // ADataType
ck::half_t, // BDataType
float, // AccDataType
ck::half_t, // CShuffleDataType
ck::Tuple<>, // DsDataType
ck::half_t, // EDataType
ck::tensor_operation::element_wise::PassThrough, // AElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // BElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // CDEElementwiseOperation
ck::tensor_operation::device::ConvolutionForwardSpecialization::
Default, // ConvForwardSpecialization
ck::tensor_operation::device::GemmSpecialization::Default, // GemmSpec
1, // NummGemmKPrefetchStage
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // KPerBlock
8, // K1
32, // MPerWmma
32, // NPerWmma
4, // MRepeat
4, // NRepeat
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_BK1
1, // BBlockLdsExtraN
1, // CShuffleMRepeatPerShuffle
1, // CShuffleNRepeatPerShuffle
ck::Sequence<
1,
32,
1,
8>, // CDEShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
8, // CDEShuffleBlockTransferScalarPerVector_NPerBlock
ck::LoopScheduler::Default, // BlkGemmPipeSched
ck::PipelineVersion::v1>; // BlkGemmPipelineVer
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::FORWARD);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.gemm_padding, ck_tile::builder::GemmPadding::DEFAULT);
EXPECT_EQ(traits.conv_specialization, ck_tile::builder::ConvSpecialization::DEFAULT);
EXPECT_EQ(traits.num_gemm_k_prefetch_stage, 1);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
EXPECT_EQ(traits.pipeline_scheduler,
ck_tile::reflect::conv::convert_pipeline_scheduler<ck::LoopScheduler::Default>());
EXPECT_EQ(traits.pipeline_version, PipelineVersion::V1);
}
// Test ConvTraits with DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3
TEST_F(ConvTraitsTest, ConvFwdTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // ALayout
ck::tensor_layout::convolution::GKYXC, // BLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWK, // ELayout
ck::half_t, // ADataType
ck::half_t, // BDataType
float, // AccDataType
ck::half_t, // CShuffleDataType
ck::Tuple<>, // DsDataType
ck::half_t, // EDataType
ck::tensor_operation::element_wise::PassThrough, // AElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // BElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // CDEElementwiseOperation
ck::tensor_operation::device::ConvolutionForwardSpecialization::
Default, // ConvForwardSpecialization
ck::tensor_operation::device::GemmSpecialization::Default, // GemmSpec
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // KPerBlock
8, // AK1
8, // BK1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_BK1
1, // BBlockLdsExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
8, // CDEBlockTransferScalarPerVector_NPerBlock
ck::BlockGemmPipelineScheduler::Intrawave, // BlkGemmPipeSched
ck::BlockGemmPipelineVersion::v1, // BlkGemmPipelineVer
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
false, // DirectLoad
1>; // NumGroupsToMerge
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::FORWARD);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.gemm_padding, ck_tile::builder::GemmPadding::DEFAULT);
EXPECT_EQ(traits.conv_specialization, ck_tile::builder::ConvSpecialization::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
// Verify A tile transfer info
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.a_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.a_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.a_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.a_tile_transfer.transfer_params.lds_padding);
// Verify B tile transfer info
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k0, 2);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.m_or_n, 128);
EXPECT_EQ(traits.b_tile_transfer.tile_dimensions.k1, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.k1, 8);
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_dims, ElementsAre(4, 64, 1));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.thread_cluster_order, ElementsAre(1, 0, 2));
EXPECT_THAT(traits.b_tile_transfer.transfer_params.src_access_order, ElementsAre(1, 0, 2));
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_vector_dim, 2);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.src_scalar_per_vector, 8);
EXPECT_EQ(traits.b_tile_transfer.transfer_params.dst_scalar_per_vector_k1, 8);
EXPECT_TRUE(traits.b_tile_transfer.transfer_params.lds_padding);
// Verify warp GEMM params
EXPECT_EQ(traits.warp_gemm.gemm_m, 32);
EXPECT_EQ(traits.warp_gemm.gemm_n, 32);
EXPECT_EQ(traits.warp_gemm.m_iter, 4);
EXPECT_EQ(traits.warp_gemm.n_iter, 4);
// Verify output tile transfer info
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.m_gemms_per_shuffle, 1);
EXPECT_EQ(traits.c_tile_transfer.shuffle_params.n_gemms_per_shuffle, 1);
EXPECT_THAT(traits.c_tile_transfer.thread_cluster_dims, ElementsAre(1, 32, 1, 8));
EXPECT_EQ(traits.c_tile_transfer.scalar_per_vector, 8);
// Verify pipeline configuration
EXPECT_EQ(traits.pipeline_scheduler, PipelineScheduler::INTRAWAVE);
EXPECT_EQ(traits.pipeline_version, PipelineVersion::V1);
}
// Test ConvTraits with DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle
TEST_F(ConvTraitsTest, ConvFwdBaseTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // ALayout
ck::tensor_layout::convolution::GKYXC, // BLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWK, // ELayout
ck::half_t, // ADataType
ck::half_t, // BDataType
float, // AccDataType
ck::half_t, // CShuffleDataType
ck::Tuple<>, // DsDataType
ck::half_t, // EDataType
ck::tensor_operation::element_wise::PassThrough, // AElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // BElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // CDEElementwiseOperation
ck::tensor_operation::device::ConvolutionForwardSpecialization::
Default, // ConvForwardSpecialization
ck::tensor_operation::device::GemmSpecialization::Default, // GemmSpec
1, // NumGemmKPrefetchStage
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // KPerBlock
8, // AK1
8, // BK1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_BK1
1, // BBlockLdsExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock
8, // CDEBlockTransferScalarPerVector_NPerBlock
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
ck::LoopScheduler::Default, // LoopSched
1>; // NumGroupsToMerge
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::FORWARD);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.gemm_padding, ck_tile::builder::GemmPadding::DEFAULT);
EXPECT_EQ(traits.conv_specialization, ck_tile::builder::ConvSpecialization::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
}
// Test ConvTraits with DeviceGroupedConvFwdMultipleD_Xdl_CShuffle_Large_Tensor
TEST_F(ConvTraitsTest, ConvFwdLargeTensorTraitsExtraction)
{
// Define a concrete instance type with specific template parameters
using DeviceInstance =
ck::tensor_operation::device::DeviceGroupedConvFwdMultipleD_Xdl_CShuffle_Large_Tensor<
2, // NDimSpatial
ck::tensor_layout::convolution::GNHWC, // ALayout
ck::tensor_layout::convolution::GKYXC, // BLayout
ck::Tuple<>, // DsLayout
ck::tensor_layout::convolution::GNHWK, // ELayout
ck::half_t, // ADataType
ck::half_t, // BDataType
float, // AccDataType
ck::half_t, // CShuffleDataType
ck::Tuple<>, // DsDataType
ck::half_t, // EDataType
ck::tensor_operation::element_wise::PassThrough, // AElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // BElementwiseOperation
ck::tensor_operation::element_wise::PassThrough, // CDEElementwiseOperation
ck::tensor_operation::device::ConvolutionForwardSpecialization::
Default, // ConvForwardSpecialization
ck::tensor_operation::device::GemmSpecialization::Default, // GemmSpec
1, // NumGemmKPrefetchStage
256, // BlockSize
128, // MPerBlock
128, // NPerBlock
16, // KPerBlock
8, // AK1
8, // BK1
32, // MPerXDL
32, // NPerXDL
4, // MXdlPerWave
4, // NXdlPerWave
ck::Sequence<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
ck::Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder
2, // ABlockTransferSrcVectorDim
8, // ABlockTransferSrcScalarPerVector
8, // ABlockTransferDstScalarPerVector_AK1
1, // ABlockLdsExtraM
ck::Sequence<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
ck::Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder
ck::Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder
2, // BBlockTransferSrcVectorDim
8, // BBlockTransferSrcScalarPerVector
8, // BBlockTransferDstScalarPerVector_BK1
1, // BBlockLdsExtraN
1, // CShuffleMXdlPerWavePerShuffle
1, // CShuffleNXdlPerWavePerShuffle
ck::Sequence<1,
32,
1,
8>, // CDEBlockTransferClusterLengths
8, // CDEBlockTransferScalarPerVector_NPerBlock
ck::half_t, // AComputeDataType
ck::half_t, // BComputeDataType
ck::LoopScheduler::Default>; // LoopSched
// Use ConvTraitsTmpl to extract compile-time information
const auto traits = ck_tile::reflect::conv::instance_to_conv_traits<DeviceInstance>();
// Verify signature information
EXPECT_EQ(traits.spatial_dim, 2);
EXPECT_EQ(traits.direction, ConvDirection::FORWARD);
EXPECT_THAT(traits.layout,
ElementsAre(TensorLayout::GNHWC, TensorLayout::GKYXC, TensorLayout::GNHWK));
EXPECT_EQ(traits.data_type, DataType::FP16);
EXPECT_EQ(traits.input_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.weight_element_op, ElementwiseOperation::PASS_THROUGH);
EXPECT_EQ(traits.output_element_op, ElementwiseOperation::PASS_THROUGH);
// Verify specializations
EXPECT_EQ(traits.gemm_padding, ck_tile::builder::GemmPadding::DEFAULT);
EXPECT_EQ(traits.conv_specialization, ck_tile::builder::ConvSpecialization::DEFAULT);
// Verify algorithm information
EXPECT_EQ(traits.thread_block_size, 256);
// Verify tile dimensions
EXPECT_EQ(traits.tile_dims.m, 128);
EXPECT_EQ(traits.tile_dims.n, 128);
EXPECT_EQ(traits.tile_dims.k, 16);
}
} // anonymous namespace