Files
composable_kernel/experimental/grouped_convolution_tile_instances/instances/instance_includes.inc
Robin Voetter cc75948d1c [CK_BUILDER] conv bwd weight testing (#3618)
* ck-builder: restructure testing conv

In order to prepare for bwd of conv testing, this commit moves some
files and types around so that we can reuse ckt::Args for both forward
and backwards convolution.

* ck-builder: decouple fwd_ck.hpp and fwd_reference.hpp from fwd.hpp

This will allow us to more easily include fwd.hpp from backwards
definitions, which is required for initializing bwd values.

* ck-builder: fix layout of test_ckb_conv_bwd_weight_xdl_cshuffle_v3

Turns out that the supplied layout isn't actually supported...

* ck-builder: ck and reference conv integration for bwd weight

* ck-builder: ck bwd weight execution test

* ck-builder: ckt::run support for ck-tile bwd weight

* ck-builder: ck tile bwd weight execution test

* ck-builder: extra debug printing in MatchesReference

* ck-builder: make ckt::run return RunResult

This type is more convenient than std::tuple, as it will allow us to
use google test matchers with this in the future.

* ck-builder: RunResult matcher

Using EXPECT_THAT(..., SuccessfulRun()) will generate a check and a nice error
message about how and why running an algorithm failed.

* ck-builder: doc fixes

* ck-builder: add missing headers
2026-01-26 23:50:15 +01:00

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#include "../../builder/test/utils/ckb_conv_tile_test_configs.hpp"
#include "ck_tile/builder/testing/conv/fwd.hpp"
#include "ck_tile/builder/testing/conv/ck_tile.hpp"
namespace ckb = ck_tile::builder;
namespace ckt = ck_tile::builder::test;
namespace cku = ck_tile::builder::test_utils;
namespace ck_tile::builder::profiling {
constexpr auto SIGNATURE_NHWGC_FP32_FWD =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::FORWARD,
.data_type = ckb::DataType::FP32,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NHWGC_BF16_FWD =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::FORWARD,
.data_type = ckb::DataType::BF16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NHWGC_FP16_FWD =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::FORWARD,
.data_type = ckb::DataType::FP16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NHWGK}}};
constexpr auto SIGNATURE_NDHWGC_FP32_FWD =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::FORWARD,
.data_type = ckb::DataType::FP32,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
constexpr auto SIGNATURE_NDHWGC_BF16_FWD =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::FORWARD,
.data_type = ckb::DataType::BF16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
constexpr auto SIGNATURE_NDHWGC_FP16_FWD =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::FORWARD,
.data_type = ckb::DataType::FP16,
.accumulation_data_type = ckb::DataType::FP32,
.input = {.config = {.layout = ckb::TensorLayout::NDHWGC}},
.weight = {.config = {.layout = ckb::TensorLayout::GKZYXC}},
.output = {.config = {.layout = ckb::TensorLayout::NDHWGK}}};
} // namespace ck_tile::builder::profiling