pandemonium_engine/editor_modules/denoise/oidn/common/tensor.h

67 lines
2.4 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. //
// ======================================================================== //
#pragma once
#include "platform.h"
#include <vector>
#include <map>
namespace oidn {
template<typename T>
using shared_vector = std::shared_ptr<std::vector<T>>;
// Generic tensor
struct Tensor
{
float* data;
std::vector<int64_t> dims;
std::string format;
shared_vector<char> buffer; // optional, only for reference counting
__forceinline Tensor() : data(nullptr) {}
__forceinline Tensor(const std::vector<int64_t>& dims, const std::string& format)
: dims(dims),
format(format)
{
buffer = std::make_shared<std::vector<char>>(size() * sizeof(float));
data = (float*)buffer->data();
}
__forceinline operator bool() const { return data != nullptr; }
__forceinline int ndims() const { return (int)dims.size(); }
// Returns the number of values
__forceinline size_t size() const
{
size_t size = 1;
for (int i = 0; i < ndims(); ++i)
size *= dims[i];
return size;
}
__forceinline float& operator [](size_t i) { return data[i]; }
__forceinline const float& operator [](size_t i) const { return data[i]; }
};
// Parses tensors from a buffer
std::map<std::string, Tensor> parseTensors(void* buffer);
} // namespace oidn