godot/thirdparty/oidn/core/network.h

113 lines
4.7 KiB
C++

// ======================================================================== //
// Copyright 2009-2019 Intel Corporation //
// //
// Licensed under the Apache License, Version 2.0 (the "License"); //
// you may not use this file except in compliance with the License. //
// You may obtain a copy of the License at //
// //
// http://www.apache.org/licenses/LICENSE-2.0 //
// //
// Unless required by applicable law or agreed to in writing, software //
// distributed under the License is distributed on an "AS IS" BASIS, //
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. //
// See the License for the specific language governing permissions and //
// limitations under the License. //
// ======================================================================== //
#include "common/tensor.h"
#include "image.h"
#include "node.h"
#include "input_reorder.h"
#include "output_reorder.h"
#include "transfer_function.h"
#pragma once
namespace oidn {
// Progress state
struct Progress
{
ProgressMonitorFunction func;
void* userPtr;
int taskCount;
};
class Executable
{
public:
virtual ~Executable() {}
virtual void execute(const Progress& progress, int taskIndex) = 0;
};
template<int K>
class Network : public Executable
{
public:
Network(const Ref<Device>& device, const std::map<std::string, Tensor>& weightMap);
void execute(const Progress& progress, int taskIndex) override;
std::shared_ptr<memory> allocTensor(const memory::dims& dims,
memory::format_tag format = memory::format_tag::any,
void* data = nullptr);
std::shared_ptr<memory> castTensor(const memory::dims& dims,
const std::shared_ptr<memory>& src,
size_t srcOffset = 0,
memory::format_tag format = memory::format_tag::any);
std::shared_ptr<memory> castTensor(const memory::dims& dims,
const std::shared_ptr<memory>& src,
const memory::dims& srcOffset);
void zeroTensor(const std::shared_ptr<memory>& dst);
memory::dims getInputReorderDims(const memory::dims& srcDims, int alignment);
std::shared_ptr<Node> addInputReorder(const Image& color,
const Image& albedo,
const Image& normal,
const std::shared_ptr<TransferFunction>& transferFunc,
int alignment,
const std::shared_ptr<memory>& userDst = nullptr);
std::shared_ptr<Node> addOutputReorder(const std::shared_ptr<memory>& src,
const std::shared_ptr<TransferFunction>& transferFunc,
const Image& output);
memory::dims getConvDims(const std::string& name, const memory::dims& srcDims);
std::shared_ptr<Node> addConv(const std::string& name,
const std::shared_ptr<memory>& src,
const std::shared_ptr<memory>& userDst = nullptr,
bool relu = true);
memory::dims getPoolDims(const memory::dims& srcDims);
std::shared_ptr<Node> addPool(const std::shared_ptr<memory>& src,
const std::shared_ptr<memory>& userDst = nullptr);
memory::dims getUpsampleDims(const memory::dims& srcDims);
std::shared_ptr<Node> addUpsample(const std::shared_ptr<memory>& src,
const std::shared_ptr<memory>& userDst = nullptr);
memory::dims getConcatDims(const memory::dims& src1Dims, const memory::dims& src2Dims);
std::shared_ptr<Node> addAutoexposure(const Image& color,
const std::shared_ptr<HDRTransferFunction>& transferFunc);
void finalize();
private:
Ref<Device> device;
engine eng;
stream sm;
std::vector<std::shared_ptr<Node>> nodes;
std::map<std::string, Tensor> weightMap;
// Memory allocation statistics
size_t activationAllocBytes = 0; // number of allocated activation bytes
size_t totalAllocBytes = 0; // total number of allocated bytes
};
} // namespace oidn