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ae4e632c7dcd168af7e2aebf9f4031315816403b
composable_kernel/experimental/grouped_convolution_tile_instances/instances/instance_includes.inc
Ville Pietilä ae4e632c7d [rocm-libraries] ROCm/rocm-libraries#4797 (commit 1a30400) 
[CK_TILE] Add CK Tile bwd weight profiler
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## Motivation

To compare old CK and CK Tile, we need to extend the current CK profiler
to support running also CK Tile instance with the same API. In order to
have the same instance coverage in CK Tile compared to the old CK, I've
added code generation from old CK configurations to CK Tile instances
using the CK Builder.

## Technical Details

- The codegen python script for CK Tile fwd convs is extended to support
also bwd weight and bwd data.
- The generated instances are added to the CMake build (target
`device_grouped_conv_bwd_weight_tile_instance`s).
- A new profiler op (`grouped_conv_bwd_weight_tile`) has been added to
the CK Profiler.
2026-03-04 21:50:29 +00:00

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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/bwd_weight.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}}};
// Backward Weight Signatures
constexpr auto SIGNATURE_NHWGC_FP32_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.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_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.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_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.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_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.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_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.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_BWD_WEIGHT =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_WEIGHT,
.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}}};
// Backward Data Signatures
constexpr auto SIGNATURE_NHWGC_FP32_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.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_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.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_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 2,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.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_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.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_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.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_BWD_DATA =
ckt::ConvSignature{.spatial_dim = 3,
.direction = ckb::ConvDirection::BACKWARD_DATA,
.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
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