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https://github.com/ROCm/composable_kernel.git
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750a87e7fc
Refactor the builder factory code into multiple files and subdirectories and a ck_tile::builder::factory namespace.
The factory implements compile-time dispatch from high-level signature and algorithm descriptors to our existing specialized convolution kernel implementations.
Major changes in this PR:
Dispatch logic is explicit in the function make_conv_instance instead of implicit in template specialization selection.
Helper code is moved to a subdirectory builder/factory/helpers.
Helpers now have unit tests.
Factories are moved to their own files.
Code moved to namespaces ck_tile::builder::factory and ck_tile::builder::factory::internal.
This does not yet fix the problem of bad error messages, but the make_conv_instance function makes the poor error messages clear. The choice of algorithm must be much more robust (perhaps with explicit enumeration in the algorithm descriptor), so that the dispatch doesn't fail.
Quality changes:
Making dispatch explicit rather than implicit will improve robustness, readability, maintainability, testability, and extensibility.
Separating code into separate files and subdirectories helps readability and extensibility.
Adding unit tests for helpers documents behavior and will enable more complex logic and functionality.
Separating files (especially unit tests) helps clarify includes and dependencies and makes code easier to refactor.
[ROCm/composable_kernel commit: 280bc42191]
199 lines
10 KiB
C++
199 lines
10 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include <gtest/gtest.h>
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#include <gmock/gmock.h>
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#include <ck_tile/builder/conv_builder.hpp>
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#include <ck_tile/builder/reflect/conv_description.hpp>
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#include "testing_utils.hpp"
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#include "impl/conv_signature_types.hpp"
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#include "impl/conv_algorithm_types.hpp"
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namespace {
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namespace ckb = ck_tile::builder;
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namespace ckr = ck_tile::reflect::conv;
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namespace ckt = ck_tile::test;
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// Defines the signature of the convolution operation to be tested.
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// This includes dimensionality, direction, data layout, and data type.
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struct ConvSignature
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{
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int spatial_dim = 2;
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ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
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ckb::DataType data_type = ckb::DataType::FP16;
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// ckb::GroupConvDeviceOp device_operation =
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// ckb::FwdGroupConvDeviceOperation::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3;
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};
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static_assert(ckb::ConvSignatureDescriptor<ConvSignature>);
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// Compile time tests for concepts
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struct ConvSignatureWithOptionalParams
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{
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int spatial_dim = 2;
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ckb::ConvDirection direction = ckb::ConvDirection::FORWARD;
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ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
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ckb::DataType data_type = ckb::DataType::FP16;
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ckb::ElementwiseOperation elementwise_operation = ckb::ElementwiseOperation::PASS_THROUGH;
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};
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static_assert(ckb::ConvSignatureDescriptor<ConvSignatureWithOptionalParams>);
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struct ConvSignatureWithInvalidOptionalParams
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{
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int spatial_dim = 2;
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ckb::ConvDirection direction = ckb::ConvDirection::FORWARD;
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ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
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ckb::DataType data_type = ckb::DataType::FP16;
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int elementwise_operation = 7; // this should fail
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// ckb::GroupConvDeviceOp device_operation =
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// ckb::FwdGroupConvDeviceOperation::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle_V3;
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};
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static_assert(!ckb::ConvSignatureDescriptor<ConvSignatureWithInvalidOptionalParams>);
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struct DefaultAlgorithm
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{
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ckb::test::ThreadBlock thread_block{.block_size = 256,
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.tile_size = {.m = 256, .n = 256, .k = 32}};
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ckb::test::GridwiseXdlGemm gridwise_gemm{.ak1 = 8,
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.bk1 = 8,
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.m_per_xdl = 16,
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.n_per_xdl = 16,
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.m_xdl_per_wave = 4,
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.n_xdl_per_wave = 4};
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ckb::test::TransferABC transfer{
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.a =
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{
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.block_transfer = {.k0 = 1, .m_n = 128, .k1 = 2},
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.lds_transfer = {.src_vector_dim = 2,
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.src_scalar_per_vector = 2,
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.lds_dst_scalar_per_vector = 2,
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.is_direct_load = false,
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.lds_padding = false},
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.block_transfer_access_order = {.order = {0, 1, 2}},
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.src_access_order = {.order = {0, 1, 2}},
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},
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.b =
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{
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.block_transfer = {.k0 = 1, .m_n = 128, .k1 = 2},
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.lds_transfer = {.src_vector_dim = 2,
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.src_scalar_per_vector = 2,
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.lds_dst_scalar_per_vector = 2,
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.is_direct_load = false,
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.lds_padding = false},
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.block_transfer_access_order = {.order = {0, 1, 2}},
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.src_access_order = {.order = {0, 1, 2}},
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},
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.c =
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{
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.thread_cluster_dims =
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{.m_block = 1, .m_wave_per_xdl = 32, .n_block = 1, .n_wave_per_xdl = 8},
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.epilogue = {.m_xdl_per_wave_per_shuffle = 1,
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.n_per_wave_per_shuffle = 1,
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.scalar_per_vector = 2},
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},
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};
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ckb::ConvFwdSpecialization fwd_specialization = ckb::ConvFwdSpecialization::DEFAULT;
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ckb::GemmSpecialization gemm_specialization = ckb::GemmSpecialization::Default;
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ckb::test::BlockGemm block_gemm{.pipeline_version = ckb::PipelineVersion::V4,
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.scheduler = ckb::PipelineScheduler::INTRAWAVE};
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};
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static_assert(ckb::ConvAlgorithmDescriptor<DefaultAlgorithm>);
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TEST(ConvDescriptionTest, DefaultInstanceHasBriefDescription)
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{
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static constexpr const ConvSignature SIGNATURE;
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static constexpr const DefaultAlgorithm ALGORITHM;
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using Instance = ckb::ConvBuilder<SIGNATURE, ALGORITHM>::Instance;
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EXPECT_THAT(ckr::Describe<Instance>().brief(), ckt::StringEqWithDiff("2D Forward convolution"));
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}
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TEST(ConvDescriptionTest, DefaultInstanceHasDetailedDescription)
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{
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static constexpr const ConvSignature SIGNATURE;
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static constexpr const DefaultAlgorithm ALGORITHM;
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using Instance = ckb::ConvBuilder<SIGNATURE, ALGORITHM>::Instance;
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EXPECT_THAT(ckr::Describe<Instance>().detailed(),
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ckt::StringEqWithDiff( //
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"2D Forward Convolution Kernel\n"
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"├─ Signature\n"
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"│ ├─ Tensor Type: FP16\n"
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"│ ├─ Memory Layout: GNHWC_GKYXC_GNHWK\n"
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"│ ├─ Input elementwise operation: PASS_THROUGH\n"
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"│ ├─ Weights elementwise operation: PASS_THROUGH\n"
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"│ └─ Output elementwise operation: PASS_THROUGH\n"
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"└─ Algorithm\n"
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" ├─ Thread block size: 256\n"
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" ├─ Data tile size: 256×256×32\n"
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" ├─ Gemm padding: DEFAULT\n"
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" ├─ Convolution specialization: DEFAULT\n"
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" ├─ Pipeline version: V4\n"
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" ├─ Pipeline scheduler: INTRAWAVE\n"
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" ├─ Warp Gemm parameters: \n"
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" │ ├─ subtile size: 16×16\n"
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" │ └─ Number of warp gemm iterations: 4×4\n"
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" └─ Memory access:\n"
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" ├─ A Tile transfer: \n"
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" │ ├─ Tile dimensions: 4×256×8×\n"
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" │ ├─ The innermost K subdimension size: 8\n"
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" │ ├─ Spatial thread distribution over the data tile: 0×1×2\n"
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" │ ├─ The order of accessing data tile axes: 0×1×2\n"
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" │ ├─ Vectorized memory access axis index (with contiguous memory): 2\n"
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" │ ├─ Vector access (GMEM read) instruction size: 2\n"
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" │ ├─ Vector access (LDS write) instruction size: 2\n"
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" │ └─ LDS data layout padding (to prevent bank conflicts): 2\n"
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" ├─ B Tile transfer: \n"
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" │ ├─ Tile dimensions: 4×256×8×\n"
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" │ ├─ The innermost K subdimension size: 8\n"
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" │ ├─ Spatial thread distribution over the data tile: 0×1×2\n"
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" │ ├─ The order of accessing data tile axes: 0×1×2\n"
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" │ ├─ Vectorized memory access axis index (with contiguous memory): 2\n"
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" │ ├─ Vector access (GMEM read) instruction size: 2\n"
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" │ ├─ Vector access (LDS write) instruction size: 2\n"
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" │ └─ LDS data layout padding (to prevent bank conflicts): 2\n"
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" └─ C Tile transfer: \n"
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" ├─ Data shuffle (number of gemm instructions per iteration): 1×1\n"
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" ├─ Spatial thread distribution used to store data: 1×32×1×8\n"
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" └─ Vector access (GMEM write) instruction size: 2"));
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}
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// NOTE: BackwardDataInstanceHasDetailedDescription test is disabled because ConvFactory
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// does not have a specialization for backward data convolutions. The test fails with:
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// "implicit instantiation of undefined template 'ck_tile::builder::ConvFactory<...>'"
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//
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// To enable this test, a ConvFactory specialization for backward data operations must be
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// implemented first.
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//
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// TEST(ConvDescriptionTest, BackwardDataInstanceHasDetailedDescription)
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// {
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// struct BackwardDataSignature
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// {
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// int spatial_dim = 2;
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// ckb::ConvDirection direction = ckb::ConvDirection::BACKWARD_DATA;
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// ckb::GroupConvLayout layout = ckb::GroupConvLayout2D::GNHWC_GKYXC_GNHWK;
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// ckb::DataType data_type = ckb::DataType::FP16;
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// ckb::ElementwiseOperation elementwise_operation =
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// ckb::ElementwiseOperation::PASS_THROUGH; ckb::GroupConvDeviceOp device_operation =
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// ckb::BwdDataGroupConvDeviceOperation::DeviceGroupedConvBwdDataMultipleD_Xdl_CShuffle_v1;
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// };
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// static_assert(ckb::ConvSignatureDescriptor<BackwardDataSignature>);
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//
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// static constexpr const BackwardDataSignature SIGNATURE;
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// static constexpr const DefaultAlgorithm ALGORITHM;
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// using Builder = ckb::ConvBuilder<SIGNATURE, ALGORITHM>;
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//
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// // Verify Brief works
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// EXPECT_THAT(ckr::Describe<Builder>().brief(),
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// ckt::StringEqWithDiff("2D Backward Data convolution"));
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//
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// // Verify detailed works - to be updated once ConvFactory is implemented
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// EXPECT_THAT(ckr::Describe<Builder>().detailed(),
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// ckt::StringEqWithDiff("PLACEHOLDER"));
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// }
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} // namespace
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