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/*
* Copyright (c) 2023-2024 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 ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE_H
#define ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE_H
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h"
#include "arm_compute/dynamic_fusion/sketch/attributes/Pool2dAttributes.h"
#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h"
#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h"
#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h"
#include "src/dynamic_fusion/utils/Utils.h"
#include "tests/CL/CLAccessor.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/reference/PoolingLayer.h"
using namespace arm_compute::experimental::dynamic_fusion;
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class DynamicFusionGpuPool2dValidationGenericFixture : public framework::Fixture
{
public:
void setup(TensorShape input_shape, const Pool2dAttributes &pool_attr, DataType data_type)
{
_target = compute_target(input_shape, pool_attr, data_type);
_reference = compute_reference(
input_shape, convert_pool_attr_to_pool_info(pool_attr, true /* mixed_precision */), data_type);
}
protected:
template <typename U>
void fill(U &&tensor, int i)
{
switch (tensor.data_type())
{
case DataType::F16:
{
arm_compute::utils::uniform_real_distribution_16bit<half> distribution{-1.0f, 1.0f};
library->fill(tensor, distribution, i);
break;
}
case DataType::F32:
{
std::uniform_real_distribution<float> distribution(-1.0f, 1.0f);
library->fill(tensor, distribution, i);
break;
}
default:
library->fill_tensor_uniform(tensor, i);
}
}
// Given input is in nchw format
TensorType compute_target(TensorShape input_shape, const Pool2dAttributes &pool_attr, const DataType data_type)
{
CLScheduler::get().default_reinit();
// Change shape due to NHWC data layout, test shapes are NCHW
permute(input_shape, PermutationVector(2U, 0U, 1U));
// Create a new workload sketch
auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
auto context = GpuWorkloadContext{&cl_compile_ctx};
GpuWorkloadSketch sketch{&context};
// Create sketch tensors
auto input_info = context.create_tensor_info(TensorInfo(input_shape, 1, data_type, DataLayout::NHWC));
auto dst_info = context.create_tensor_info();
// Create Pool2dSettings
GpuPool2dSettings pool_settings = GpuPool2dSettings();
ITensorInfo *ans_info = FunctionType::create_op(sketch, input_info, pool_attr, pool_settings);
GpuOutput::create_op(sketch, ans_info, dst_info);
// Configure runtime
ClWorkloadRuntime runtime;
runtime.configure(sketch);
// (Important) Allocate auxiliary tensor memory if there are any
for (auto &data : runtime.get_auxiliary_tensors())
{
CLTensor *tensor = std::get<0>(data);
TensorInfo info = std::get<1>(data);
AuxMemoryInfo aux_mem_req = std::get<2>(data);
tensor->allocator()->init(info, aux_mem_req.alignment);
tensor->allocator()->allocate(); // Use ACL allocated memory
}
// Construct user tensors
TensorType t_input{};
TensorType t_dst{};
// Initialize user tensors
t_input.allocator()->init(*input_info);
t_dst.allocator()->init(*dst_info);
// Allocate and fill user tensors
t_input.allocator()->allocate();
t_dst.allocator()->allocate();
fill(AccessorType(t_input), 0);
// Run runtime
runtime.run({&t_input, &t_dst});
return t_dst;
}
SimpleTensor<T> compute_reference(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type)
{
// Create reference
SimpleTensor<T> src(shape, data_type, 1, QuantizationInfo());
// Fill reference
fill(src, 0);
return reference::pooling_layer<T>(src, pool_info, QuantizationInfo(), nullptr, DataLayout::NCHW);
}
TensorType _target{};
SimpleTensor<T> _reference{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class DynamicFusionGpuPool2dValidationFixture
: public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
void setup(TensorShape input_shape,
PoolingType pool_type,
Size2D pool_size,
Padding2D pad,
Size2D stride,
bool exclude_padding,
DataType data_type)
{
DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(
input_shape,
Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(
exclude_padding),
data_type);
}
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class DynamicFusionGpuPool2dSpecialValidationFixture
: public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
void setup(TensorShape input_shape, Pool2dAttributes pool_attr, DataType data_type)
{
DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(
input_shape, pool_attr, data_type);
}
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif // ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE_H
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