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/*
* Copyright (c) 2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION
#error "This experimental feature must be enabled with -DENABLE_EXPERIMENTAL_DYNAMIC_FUSION"
#endif /* ENABLE_EXPERIMENTAL_DYNAMIC_FUSION */
#include "src/gpu/cl/kernels/experimental/dynamic_fusion/ClCompositeKernel.h"
#include "src/core/experimental/dynamic_fusion/ClKernelBuildingAPI.h"
#include "src/core/utils/helpers/float_ops.h"
#include "src/gpu/cl/kernels/ClElementwiseKernel.h"
#include "src/gpu/cl/kernels/ClGemmMatrixMultiplyNativeKernel.h"
#include "tests/CL/CLAccessor.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "tests/validation/Validation.h"
#include "tests/validation/reference/ConvolutionLayer.h"
#include "tests/validation/reference/ElementwiseOperations.h"
#include "tests/validation/reference/GEMM.h"
#include "tests/validation/reference/Permute.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "src/core/AccessWindowStatic.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "tests/validation/CL/UNIT/dynamic_fusion/Utils.h"
#include <chrono>
using namespace arm_compute::experimental::dynamic_fusion;
using namespace arm_compute::test::validation::utils;
namespace arm_compute
{
namespace test
{
namespace validation
{
TEST_SUITE(CL)
TEST_SUITE(UNIT)
TEST_SUITE(DYNAMIC_FUSION)
TEST_SUITE(ClCompositeKernel)
TEST_SUITE(Validate)
TEST_CASE(MoveNet_SubGraph_1_DirectConv2d, framework::DatasetMode::ALL)
{
/* Computation:
* out = add(addend, direct_conv2d(lhs, rhs, bias)) (non-broadcast)
*/
ClCompositeKernel kernel{};
ClKernelBlueprint bp{};
ClKernelCode cl_code{};
ClExecutionDescriptor exec_desc{};
Status st{};
const auto data_type = DataType::F32;
const auto conv_info = Conv2dDescriptor{ Padding2D{ 1U, 1U, 1U, 1U }, { 1U, 1U } /* stride */ };
const auto width = 7U;
const auto height = 6U;
const auto IFM = 5U;
const auto OFM = 4U;
const auto kernel_sz = 3U;
const auto src_shape = TensorShape(IFM, width, height);
const auto wei_shape = TensorShape(IFM, kernel_sz, kernel_sz, OFM);
const auto bia_shape = TensorShape(OFM);
const auto addend_shape = TensorShape(1, 1);
const auto dst_shape = TensorShape(OFM, width, height);
auto src_info = TensorInfo(src_shape, 1, data_type, DataLayout::NHWC);
auto wei_info = TensorInfo(wei_shape, 1, data_type, DataLayout::NHWC);
auto bia_info = TensorInfo(bia_shape, 1, data_type, DataLayout::NHWC);
auto addend_info = TensorInfo(addend_shape, 1, data_type, DataLayout::NHWC);
auto dst_info = TensorInfo(dst_shape, 1, data_type, DataLayout::NHWC);
const auto n0 = std::min(OFM, 4u);
const auto m0 = (OFM > 16) ? ((data_type == DataType::F32) ? 2U : 4U) : 1U;
const ClDirectConv2dKernelDescriptor direct_conv2d_desc{ conv_info };
const ClEltwiseAddKernelDescriptor eltwise_add_desc{};
const TileDescriptor store_tile_info{ Size2D(n0, m0), Size2D(width, height), ClippingStrategy::TOP_LEFT };
ArgumentID src_id{ g_arg_placeholder };
ArgumentID wei_id{ g_arg_placeholder };
ArgumentID bia_id{ g_arg_placeholder };
ArgumentID acc_id{ g_arg_placeholder };
ArgumentID acc_1_id{ g_arg_placeholder };
ArgumentID addend_id{ g_arg_placeholder };
ArgumentID dst_id{ g_arg_placeholder };
st = add_tensor(bp, &src_info, src_id);
st = add_tensor(bp, &wei_info, wei_id);
st = add_tensor(bp, &bia_info, bia_id);
st = add_tensor(bp, &dst_info, acc_id);
st = add_tensor(bp, &dst_info, acc_1_id);
st = add_tensor(bp, &addend_info, addend_id);
st = add_tensor(bp, &dst_info, dst_id);
st = add_kcomp_direct_conv2d(bp, direct_conv2d_desc, src_id, wei_id, bia_id, acc_id);
st = add_kcomp_eltwise_add(bp, eltwise_add_desc, addend_id, acc_id, acc_1_id);
st = add_kcomp_store(bp, StoreType::TStoreIndirectWidthSelect, acc_1_id, dst_id);
exec_desc.skip_sliding_window = true;
st = set_tile_info(bp, store_tile_info);
st = build(cl_code, ClCodeBuilderContext{ GpuInfo{ GPUTarget::G71 } }, bp);
st = tune_static(exec_desc, cl_code);
CLScheduler::get().default_reinit();
kernel.configure(CLKernelLibrary::get().get_compile_context(), cl_code);
// Construct tensors
CLTensor src{};
CLTensor wei{};
CLTensor bia{};
CLTensor addend{};
CLTensor dst{};
// Init tensors
src.allocator()->init(src_info);
wei.allocator()->init(wei_info);
bia.allocator()->init(bia_info);
addend.allocator()->init(dst_info);
dst.allocator()->init(dst_info);
// "Pack" tensors
ITensorPack tensors{ { src_id, &src },
{ wei_id, &wei },
{ bia_id, &bia },
{ addend_id, &addend },
{ dst_id, &dst } };
// Allocate and fill tensors
src.allocator()->allocate();
wei.allocator()->allocate();
bia.allocator()->allocate();
addend.allocator()->allocate();
dst.allocator()->allocate();
fill<float>(CLAccessor(src), 0, library.get());
fill<float>(CLAccessor(wei), 1, library.get());
fill<float>(CLAccessor(bia), 2, library.get());
fill<float>(CLAccessor(addend), 3, library.get());
CLScheduler::get().enqueue_op(kernel, tensors, exec_desc, true);
// Create reference
SimpleTensor<float> ref_src_nhwc{ src_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC };
SimpleTensor<float> ref_wei_nhwc{ wei_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC };
SimpleTensor<float> ref_bia_nhwc{ bia_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC };
SimpleTensor<float> ref_addend_nhwc{ dst_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC };
// Fill reference
fill<float>(ref_src_nhwc, 0, library.get());
fill<float>(ref_wei_nhwc, 1, library.get());
fill<float>(ref_bia_nhwc, 2, library.get());
fill<float>(ref_addend_nhwc, 3, library.get());
auto ref_src = reference::permute(ref_src_nhwc, PermutationVector(1U, 2U, 0U));
auto ref_wei = reference::permute(ref_wei_nhwc, PermutationVector(1U, 2U, 0U));
auto ref_bia = reference::permute(ref_bia_nhwc, PermutationVector(1U, 2U, 0U));
auto ref_addend = reference::permute(ref_addend_nhwc, PermutationVector(1U, 2U, 0U));
TensorShape dst_shape_nchw{ dst_shape };
permute(dst_shape_nchw, PermutationVector(1U, 2U, 0U));
const auto ref_dst = reference::arithmetic_operation(
ArithmeticOperation::ADD,
ref_addend,
reference::convolution_layer<float>(ref_src, ref_wei, ref_bia, dst_shape_nchw,
PadStrideInfo
{
static_cast<unsigned int>(conv_info.stride.x()),
static_cast<unsigned int>(conv_info.stride.y()),
static_cast<unsigned int>(conv_info.pad.left),
static_cast<unsigned int>(conv_info.pad.top) }),
data_type,
ConvertPolicy::SATURATE);
RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
validate(CLAccessor(dst), ref_dst, tolerance_f32);
}
TEST_SUITE_END() // Validate
TEST_SUITE_END() // ClCompositeKernel
TEST_SUITE_END() // DYNAMIC_FUSION
TEST_SUITE_END() // UNIT
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute
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