BufferStore.h

// Copyright 2024, UChicago Argonne, LLC
// All Rights Reserved
// Software Name: NEML2 -- the New Engineering material Model Library, version 2
// By: Argonne National Laboratory
// OPEN SOURCE LICENSE (MIT)
//
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// of this software and associated documentation files (the "Software"), to deal
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// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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// furnished to do so, subject to the following conditions:
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// The above copyright notice and this permission notice shall be included in
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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#pragma once
 
#include "neml2/base/NEML2Object.h"
#include "neml2/base/OptionSet.h"
#include "neml2/base/Storage.h"
#include "neml2/tensors/TensorValue.h"
 
// The following are not directly used by BufferStore itself.
// We put them here so that derived classes can add expected options of these types.
#include "neml2/base/CrossRef.h"
#include "neml2/base/EnumSelection.h"
#include "neml2/tensors/tensors.h"
 
namespace neml2
{
class BufferStore
{
public:
  BufferStore(OptionSet options, NEML2Object * object);
 
  BufferStore(const BufferStore &) = delete;
  BufferStore(BufferStore &&) = delete;
  BufferStore & operator=(const BufferStore &) = delete;
  BufferStore & operator=(BufferStore &&) = delete;
  virtual ~BufferStore() = default;
 
  const Storage<std::string, TensorValueBase> & named_buffers() const
  {
    // NOLINTNEXTLINE(cppcoreguidelines-pro-type-const-cast)
    return const_cast<BufferStore *>(this)->named_buffers();
  }
  Storage<std::string, TensorValueBase> & named_buffers();
 
  TensorValueBase & get_buffer(const std::string & name);
 
  const TensorValueBase & get_buffer(const std::string & name) const;
 
protected:
  virtual void send_buffers_to(const torch::TensorOptions & options);
 
  template <typename T, typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
  const T & declare_buffer(const std::string & name, const T & rawval);
 
  template <typename T, typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
  const T & declare_buffer(const std::string & name, const CrossRef<T> & crossref);
 
  template <typename T, typename = typename std::enable_if_t<std::is_base_of_v<TensorBase<T>, T>>>
  const T & declare_buffer(const std::string & name, const std::string & input_option_name);
 
private:
  NEML2Object * _object;
 
  const OptionSet _object_options;
 
  Storage<std::string, TensorValueBase> _buffer_values;
};
 
} // namespace neml2