GpuFsaConvolution2d.cpp

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//
// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "GpuFsaConvolution2d.hpp"
#include "UtilsGpuFsa.hpp"
 
#include <aclCommon/ArmComputeTensorUtils.hpp>
 
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuConv2d.h>
#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h>
 
#include <vector>
 
using namespace arm_compute::experimental::dynamic_fusion;
using namespace armnn::armcomputetensorutils;
 
namespace armnn
{
 
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::ITensorInfo* 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());
 
        biasSketchInfoPtr = workloadContext.create_tensor_info(aclBiasInfo);
    }
 
    Conv2dAttributes conv2dAttributes = CreateConv2dAttributes(descriptor);
 
    // 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 GpuFsa 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 inputTensorinfos / outputTensorInfos, these are pointers to the TensorInfos used when creating the sketch.
 * They refer to the TensorInfos stored within the GpuWorkloadContext and are needed when executing the sketch
 * as the TensorInfos used when creating the Tensors must match those used to create the Sketch. Otherwise the runtime
 * doesn't know which Tensors to use.
 */
    GpuWorkloadSketch* sketch = blob->sketch.get();
    GpuWorkloadContext* workloadContext = blob->workloadContext.get();
    std::vector<arm_compute::ITensorInfo*> inputTensorInfos = {};
    std::vector<arm_compute::ITensorInfo*> outputTensorInfos = {};
 
    // 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());
 
    inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclInputInfo));
    inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclWeightsInfo));
 
    // Only create the bias tensor info if enabled, otherwise pass nullptr to validate_op / create_op
    arm_compute::TensorInfo aclBiasInfo;
    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());
 
        inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclBiasInfo));
        biasSketchInfoPtr = inputTensorInfos[2];
    }
 
    Conv2dAttributes conv2dAttributes = CreateConv2dAttributes(descriptor);
 
    // Validate operator, check status and update reasonIfUnsupported
    arm_compute::Status aclStatus = GpuConv2d::validate_op(*sketch,
                                                           inputTensorInfos[0],
                                                           inputTensorInfos[1],
                                                           biasSketchInfoPtr,
                                                           conv2dAttributes);
 
    const bool supported = (aclStatus.error_code() == arm_compute::ErrorCode::OK);
    if (!supported)
    {
        throw BackendCapabilityException("\"GpuFsa\" backend failed during Convolution2D operation validation");
    }
 
    // Create the Op within the Sketch using the TensorInfos we have stored
    arm_compute::ITensorInfo* convOutInfo = GpuConv2d::create_op(*sketch,
                                                                 inputTensorInfos[0],
                                                                 inputTensorInfos[1],
                                                                 biasSketchInfoPtr,
                                                                 conv2dAttributes);
 
    // Create the Output
    outputTensorInfos.emplace_back(workloadContext->create_tensor_info());
    GpuOutput::create_op(*sketch, convOutInfo, outputTensorInfos[0]);
 
    // Store the TensorInfos within the blob as unique_ptrs to be used later
    blob->inputTensorInfos = std::make_unique<std::vector<arm_compute::ITensorInfo*>>(inputTensorInfos);
    blob->outputTensorInfos = std::make_unique<std::vector<arm_compute::ITensorInfo*>>(outputTensorInfos);
}
 
} // namespace armnn