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composable_kernel/experimental/builder/test/test_conv_description.cpp
John Shumway f29b67cf9b [CK_BUILDER] Add Description::instance_string() method and update tests (#3340)
* Create Description::instance_string() function

To expose more reflection capabilities in MIOpen, we add the instance_string functionality to the ckr::Description class. This PR introduces a base class, adds the instance_string method, and implements the method by injecting the Traits::instance_string method through the ConvDescription constructor.

This will enable us to replace the specialized get_instance_string() method on device operations with a describe() method in a subsequent PR.

* Test describe().instance_string()

Update the instance string tests to also call `ckr::describe<Instance>().instance_string()`. This documents that the xld kernels are supported with describe(), but WMMA and DL kernels are not yet supported. Also update namespace and add a HasConvTraits concept.
2025-12-03 06:36:09 -08:00

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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <gtest/gtest.h>
#include <gmock/gmock.h>
#include <ck_tile/builder/conv_builder.hpp>
#include <ck_tile/builder/reflect/conv_description.hpp>
#include "testing_utils.hpp"
#include "impl/conv_signature_types.hpp"
#include "impl/conv_algorithm_types.hpp"
namespace {
namespace ckb = ck_tile::builder;
namespace ckr = ck_tile::reflect;
namespace ckt = ck_tile::test;
// Defines the signature of the convolution operation to be tested.
// This includes dimensionality, direction, data layout, and data type.
struct ConvSignature
{
int spatial_dim = 2;
ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
ckb::DataType data_type = ckb::DataType::FP16;
// ckb::GroupConvDeviceOp device_operation =
// ckb::FwdGroupConvDeviceOperation::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3;
};
static_assert(ckb::ConvSignatureDescriptor<ConvSignature>);
// Compile time tests for concepts
struct ConvSignatureWithOptionalParams
{
int spatial_dim = 2;
ckb::ConvDirection direction = ckb::ConvDirection::FORWARD;
ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
ckb::DataType data_type = ckb::DataType::FP16;
ckb::ElementwiseOperation elementwise_operation = ckb::ElementwiseOperation::PASS_THROUGH;
};
static_assert(ckb::ConvSignatureDescriptor<ConvSignatureWithOptionalParams>);
struct ConvSignatureWithInvalidOptionalParams
{
int spatial_dim = 2;
ckb::ConvDirection direction = ckb::ConvDirection::FORWARD;
ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
ckb::DataType data_type = ckb::DataType::FP16;
int elementwise_operation = 7; // this should fail
// ckb::GroupConvDeviceOp device_operation =
// ckb::FwdGroupConvDeviceOperation::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3;
};
static_assert(!ckb::ConvSignatureDescriptor<ConvSignatureWithInvalidOptionalParams>);
struct DefaultAlgorithm
{
ckb::test::ThreadBlock thread_block{.block_size = 256,
.tile_size = {.m = 256, .n = 256, .k = 32}};
ckb::test::GridwiseXdlGemm gridwise_gemm{.ak1 = 8,
.bk1 = 8,
.m_per_xdl = 16,
.n_per_xdl = 16,
.m_xdl_per_wave = 4,
.n_xdl_per_wave = 4};
ckb::test::TransferABC transfer{
.a =
{
.block_transfer = {.k0 = 1, .m_n = 128, .k1 = 2},
.lds_transfer = {.src_vector_dim = 2,
.src_scalar_per_vector = 2,
.lds_dst_scalar_per_vector = 2,
.is_direct_load = false,
.lds_padding = false},
.block_transfer_access_order = {.order = {0, 1, 2}},
.src_access_order = {.order = {0, 1, 2}},
},
.b =
{
.block_transfer = {.k0 = 1, .m_n = 128, .k1 = 2},
.lds_transfer = {.src_vector_dim = 2,
.src_scalar_per_vector = 2,
.lds_dst_scalar_per_vector = 2,
.is_direct_load = false,
.lds_padding = false},
.block_transfer_access_order = {.order = {0, 1, 2}},
.src_access_order = {.order = {0, 1, 2}},
},
.c =
{
.thread_cluster_dims =
{.m_block = 1, .m_wave_per_xdl = 32, .n_block = 1, .n_wave_per_xdl = 8},
.epilogue = {.m_xdl_per_wave_per_shuffle = 1,
.n_per_wave_per_shuffle = 1,
.scalar_per_vector = 2},
},
};
ckb::ConvFwdSpecialization fwd_specialization = ckb::ConvFwdSpecialization::DEFAULT;
ckb::GemmSpecialization gemm_specialization = ckb::GemmSpecialization::Default;
ckb::test::BlockGemm block_gemm{.pipeline_version = ckb::PipelineVersion::V4,
.scheduler = ckb::PipelineScheduler::INTRAWAVE};
};
static_assert(ckb::ConvAlgorithmDescriptor<DefaultAlgorithm>);
TEST(ConvDescriptionTest, DefaultInstanceHasBriefDescription)
{
static constexpr const ConvSignature SIGNATURE;
static constexpr const DefaultAlgorithm ALGORITHM;
using Instance = ckb::ConvBuilder<SIGNATURE, ALGORITHM>::Instance;
EXPECT_THAT(ckr::describe<Instance>().brief(), ckt::StringEqWithDiff("2D Forward convolution"));
}
TEST(ConvDescriptionTest, DefaultInstanceHasDetailedDescription)
{
static constexpr const ConvSignature SIGNATURE;
static constexpr const DefaultAlgorithm ALGORITHM;
using Instance = ckb::ConvBuilder<SIGNATURE, ALGORITHM>::Instance;
EXPECT_THAT(ckr::describe<Instance>().detailed(),
ckt::StringEqWithDiff( //
"2D Forward Convolution Kernel\n"
"├─ Signature\n"
"│ ├─ Tensor Type: FP16\n"
"│ ├─ Memory Layout: GNHWC_GKYXC_GNHWK\n"
"│ ├─ Input elementwise operation: PASS_THROUGH\n"
"│ ├─ Weights elementwise operation: PASS_THROUGH\n"
"│ └─ Output elementwise operation: PASS_THROUGH\n"
"└─ Algorithm\n"
" ├─ Thread block size: 256\n"
" ├─ Data tile size: 256×256×32\n"
" ├─ Gemm padding: DEFAULT\n"
" ├─ Convolution specialization: DEFAULT\n"
" ├─ Pipeline version: V4\n"
" ├─ Pipeline scheduler: INTRAWAVE\n"
" ├─ Warp Gemm parameters: \n"
" │ ├─ subtile size: 16×16\n"
" │ └─ Number of warp gemm iterations: 4×4\n"
" └─ Memory access:\n"
" ├─ A Tile transfer: \n"
" │ ├─ Tile dimensions: 4×256×8×\n"
" │ ├─ The innermost K subdimension size: 8\n"
" │ ├─ Spatial thread distribution over the data tile: 0×1×2\n"
" │ ├─ The order of accessing data tile axes: 0×1×2\n"
" │ ├─ Vectorized memory access axis index (with contiguous memory): 2\n"
" │ ├─ Vector access (GMEM read) instruction size: 2\n"
" │ ├─ Vector access (LDS write) instruction size: 2\n"
" │ └─ LDS data layout padding (to prevent bank conflicts): 2\n"
" ├─ B Tile transfer: \n"
" │ ├─ Tile dimensions: 4×256×8×\n"
" │ ├─ The innermost K subdimension size: 8\n"
" │ ├─ Spatial thread distribution over the data tile: 0×1×2\n"
" │ ├─ The order of accessing data tile axes: 0×1×2\n"
" │ ├─ Vectorized memory access axis index (with contiguous memory): 2\n"
" │ ├─ Vector access (GMEM read) instruction size: 2\n"
" │ ├─ Vector access (LDS write) instruction size: 2\n"
" │ └─ LDS data layout padding (to prevent bank conflicts): 2\n"
" └─ C Tile transfer: \n"
" ├─ Data shuffle (number of gemm instructions per iteration): 1×1\n"
" ├─ Spatial thread distribution used to store data: 1×32×1×8\n"
" └─ Vector access (GMEM write) instruction size: 2"));
}
TEST(ConvDescriptionTest, DefaultInstanceHasInstanceString)
{
static constexpr const ConvSignature SIGNATURE;
static constexpr const DefaultAlgorithm ALGORITHM;
using Instance = ckb::ConvBuilder<SIGNATURE, ALGORITHM>::Instance;
// Get the instance string from the description
std::string instance_str = ckr::describe<Instance>().instance_string();
// Verify that the instance string is not empty
EXPECT_FALSE(instance_str.empty());
// Verify that it contains the device operation name
// The exact format depends on the InstanceTraits implementation
EXPECT_THAT(instance_str, ::testing::HasSubstr("DeviceGroupedConvFwdMultipleABD"));
}
// NOTE: BackwardDataInstanceHasDetailedDescription test is disabled because ConvFactory
// does not have a specialization for backward data convolutions. The test fails with:
// "implicit instantiation of undefined template 'ck_tile::builder::ConvFactory<...>'"
//
// To enable this test, a ConvFactory specialization for backward data operations must be
// implemented first.
//
// TEST(ConvDescriptionTest, BackwardDataInstanceHasDetailedDescription)
// {
// struct BackwardDataSignature
// {
// int spatial_dim = 2;
// ckb::ConvDirection direction = ckb::ConvDirection::BACKWARD_DATA;
// ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
// ckb::DataType data_type = ckb::DataType::FP16;
// ckb::ElementwiseOperation elementwise_operation =
// ckb::ElementwiseOperation::PASS_THROUGH; ckb::GroupConvDeviceOp device_operation =
// ckb::BwdDataGroupConvDeviceOperation::DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1;
// };
// static_assert(ckb::ConvSignatureDescriptor<BackwardDataSignature>);
//
// static constexpr const BackwardDataSignature SIGNATURE;
// static constexpr const DefaultAlgorithm ALGORITHM;
// using Builder = ckb::ConvBuilder<SIGNATURE, ALGORITHM>;
//
// // Verify Brief works
// EXPECT_THAT(ckr::Describe<Builder>().brief(),
// ckt::StringEqWithDiff("2D Backward Data convolution"));
//
// // Verify detailed works - to be updated once ConvFactory is implemented
// EXPECT_THAT(ckr::Describe<Builder>().detailed(),
// ckt::StringEqWithDiff("PLACEHOLDER"));
// }
} // namespace