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//
// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "GpuFsaConvolution2d.hpp"
#include <armnn/Types.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <arm_compute/core/ITensorInfo.h>
#include <arm_compute/core/TensorInfo.h>
#include <arm_compute/core/TensorShape.h>
#include <arm_compute/core/CL/CLKernelLibrary.h>
#include <arm_compute/core/CL/CLCompileContext.h>
#include <arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h>
#include <src/dynamic_fusion/sketch/gpu/GpuWorkloadContextImpl.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuConv2d.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h>
#include <vector>
#include <iostream>
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status GpuFsaConvolution2dValidate(const TensorInfo& input,
const Convolution2dDescriptor& descriptor,
const TensorInfo& weights,
const Optional<TensorInfo>& biases)
{
// Create a new workload sketch, for validation purposes
auto compileCtx = arm_compute::CLKernelLibrary::get().get_compile_context();
auto workloadContext = GpuWorkloadContext(&compileCtx);
GpuWorkloadSketch sketch{ &workloadContext };
// Build and create tensor infos using the sketch
const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
aclWeightsInfo.set_are_values_constant(weights.IsConstant());
auto inputInfo = workloadContext.create_tensor_info(aclInputInfo);
auto weightInfo = workloadContext.create_tensor_info(aclWeightsInfo);
// Only create the bias tensor info if enabled, otherwise pass nullptr to validate_op
arm_compute::TensorInfo aclBiasInfo;
arm_compute::TensorInfo biasSketchInfo;
arm_compute::TensorInfo* biasSketchInfoPtr = nullptr;
if (descriptor.m_BiasEnabled)
{
if(!biases.has_value())
{
throw InvalidArgumentException("GpuFsaConvolution2d::ValidateOp: No biases set when biases are enabled");
}
aclBiasInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
aclBiasInfo.set_are_values_constant(biases.value().IsConstant());
biasSketchInfo = workloadContext.create_tensor_info(aclBiasInfo);
biasSketchInfoPtr = &biasSketchInfo;
}
// Set Conv2d attributes using descriptor
const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(descriptor.m_DilationX,
descriptor.m_DilationY);
const arm_compute::Padding2D aclPadInfo = BuildArmComputePaddingInfo(descriptor);
const arm_compute::Size2D aclStrideInfo = BuildArmComputeSize2D(descriptor.m_StrideX, descriptor.m_StrideY);
Conv2dAttributes conv2DAttributes{};
conv2DAttributes.dilation(aclDilationInfo);
conv2DAttributes.pad(aclPadInfo);
conv2DAttributes.stride(aclStrideInfo);
// Validate operator, check status and update reasonIfUnsupported
arm_compute::Status aclStatus = GpuConv2d::validate_op(sketch,
&inputInfo,
&weightInfo,
biasSketchInfoPtr,
conv2DAttributes);
return aclStatus;
}
void GpuFsaConvolution2dCreateOp(GpuFsaPreCompiledBlob* blob,
const TensorInfo& input,
const Convolution2dDescriptor& descriptor,
const TensorInfo& weights,
const Optional<TensorInfo>& biases)
{
/*
* Creating an Op for the GpuFds backend requires us to create and maintain quite a bit of data, which is then stored
* in a GpuFsaPreCompiledBlob for execution later. Specifically we need:
* GpuWorkloadContext, this contains the TensorInfos and is unique to the Graph being executed
* Sketch, this is similar to a subgraph and can contain one or more operations. Multiple ops can be "fused" together
* using a single sketch.
* The TensorInfoIds, these are the ids of the TensorInfos used when creating the sketch. They refer to the TensorInfos
* stored within the GpuWorkloadContext and are used to fetch them later when executing the sketch.
*/
using namespace arm_compute::experimental::dynamic_fusion;
GpuWorkloadSketch* sketch = blob->sketch.get();
GpuWorkloadContext* workloadContext = blob->workloadContext.get();
std::vector<int32_t> inputIds = {};
std::vector<int32_t> outputIds = {};
// Build and create tensor infos using the sketch
const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
aclWeightsInfo.set_are_values_constant(weights.IsConstant());
auto inputInfo = workloadContext->create_tensor_info(aclInputInfo);
aclWeightsInfo.set_are_values_constant(weights.IsConstant());
inputIds.emplace_back(inputInfo.id());
auto weightInfo = workloadContext->create_tensor_info(aclWeightsInfo);
inputIds.emplace_back(weightInfo.id());
// Only create the bias tensor info if enabled, otherwise pass nullptr to validate_op
arm_compute::TensorInfo aclBiasInfo;
arm_compute::TensorInfo biasSketchInfo;
arm_compute::ITensorInfo* biasSketchInfoPtr = nullptr;
if (descriptor.m_BiasEnabled)
{
if(!biases.has_value())
{
throw InvalidArgumentException("GpuFsaConvolution2d::CreateOp: No biases set when biases are enabled");
}
aclBiasInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
aclBiasInfo.set_are_values_constant(biases.value().IsConstant());
biasSketchInfo = workloadContext->create_tensor_info(aclBiasInfo);
inputIds.emplace_back(biasSketchInfo.id());
biasSketchInfoPtr = workloadContext->implementation().get_tensor_info(biasSketchInfo.id());
}
// Set Conv2d attributes using descriptor
const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(descriptor.m_DilationX,
descriptor.m_DilationY);
const arm_compute::Padding2D aclPadInfo = BuildArmComputePaddingInfo(descriptor);
const arm_compute::Size2D aclStrideInfo = BuildArmComputeSize2D(descriptor.m_StrideX, descriptor.m_StrideY);
Conv2dAttributes conv2DAttributes{};
conv2DAttributes.dilation(aclDilationInfo);
conv2DAttributes.pad(aclPadInfo);
conv2DAttributes.stride(aclStrideInfo);
// Validate operator, check status and update reasonIfUnsupported
arm_compute::Status aclStatus =
GpuConv2d::validate_op(*sketch,
workloadContext->implementation().get_tensor_info(inputInfo.id()),
workloadContext->implementation().get_tensor_info(weightInfo.id()),
biasSketchInfoPtr,
conv2DAttributes);
const bool supported = (aclStatus.error_code() == arm_compute::ErrorCode::OK);
if (!supported)
{
throw BackendCapabilityException("\"GpuFsa\" backend failed during Convolution2D operation validation");
}
arm_compute::ITensorInfo* convOutInfo =
GpuConv2d::create_op(*sketch,
workloadContext->implementation().get_tensor_info(inputInfo.id()),
workloadContext->implementation().get_tensor_info(weightInfo.id()),
biasSketchInfoPtr,
conv2DAttributes);
arm_compute::TensorInfo outputDstInfo = workloadContext->create_tensor_info();
outputIds.emplace_back(outputDstInfo.id());
GpuOutput::create_op(*sketch, convOutInfo, workloadContext->implementation().get_tensor_info(outputDstInfo.id()));
blob->inputIds = std::make_unique<std::vector<int32_t>>(inputIds);
blob->outputIds = std::make_unique<std::vector<int32_t>>(outputIds);
}
} // namespace armnn
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