assembly.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
// all copies or substantial portions of the Software.
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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,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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#pragma once
 
#include "neml2/misc/types.h"
 
namespace neml2
{
class Tensor;
template <std::size_t N>
class Derivative;

Tensor pop_intrsc_intmd_dim(const Tensor & t, Size dim);

Tensor push_intrsc_intmd_dim(const Tensor & t, Size dim);

Tensor pop_intrsc_intmd_dim(const Derivative<1> & deriv);

template <std::size_t N>
Tensor pop_intrsc_intmd_dim(const Tensor & from,
                            const std::array<std::size_t, N> & intrsc_intmd_dims,
                            const std::array<TensorShape, N> & base_shapes,
                            const std::string & debug_name = "<anonymous>");

template <std::size_t N>
Tensor push_intrsc_intmd_dim(const Tensor & from,
                             const std::array<std::size_t, N> & intrsc_intmd_dims,
                             const std::array<TensorShape, N> & base_shapes,
                             const std::string & debug_name = "<anonymous>");

template <std::size_t N>
Tensor from_assembly(const Tensor & from,
                     const std::array<TensorShape, N> & intmd_shapes,
                     const std::array<TensorShape, N> & base_shapes);

template <std::size_t N>
Tensor to_assembly(const Tensor & from,
                   const std::array<TensorShape, N> & intmd_shapes,
                   const std::array<TensorShape, N> & base_shapes);
}