BatchTensorBase.h

// Copyright 2023, 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)
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// 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:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// 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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// THE SOFTWARE.
 
#pragma once
 
#include "neml2/misc/utils.h"
 
namespace neml2
{
// Forward declarations
template <class Derived>
class BatchTensorBase;
 
class BatchTensor;
 
template <class Derived>
class BatchTensorBase : public torch::Tensor
{
public:
  BatchTensorBase() = default;
 
  BatchTensorBase(const torch::Tensor & tensor, TorchSize batch_dim);
 
  BatchTensorBase(const Derived & tensor);
 
  BatchTensorBase(Real) = delete;
 
  [[nodiscard]] static Derived empty_like(const Derived & other);
  [[nodiscard]] static Derived zeros_like(const Derived & other);
  [[nodiscard]] static Derived ones_like(const Derived & other);
  [[nodiscard]] static Derived full_like(const Derived & other, Real init);
 
  [[nodiscard]] static Derived linspace(const Derived & start,
                                        const Derived & end,
                                        TorchSize nstep,
                                        TorchSize dim = 0,
                                        TorchSize batch_dim = -1);
  [[nodiscard]] static Derived logspace(const Derived & start,
                                        const Derived & end,
                                        TorchSize nstep,
                                        TorchSize dim = 0,
                                        TorchSize batch_dim = -1,
                                        Real base = 10);
 
  bool batched() const;
 
  TorchSize batch_dim() const;
 
  TorchSize & batch_dim();
 
  TorchSize base_dim() const;
 
  TorchShapeRef batch_sizes() const;
 
  TorchSize batch_size(TorchSize index) const;
 
  TorchShapeRef base_sizes() const;
 
  TorchSize base_size(TorchSize index) const;
 
  TorchSize base_storage() const;
 
  Derived batch_index(TorchSlice indices) const;
 
  BatchTensor base_index(const TorchSlice & indices) const;
 
  void batch_index_put(TorchSlice indices, const torch::Tensor & other);
 
  void base_index_put(const TorchSlice & indices, const torch::Tensor & other);
 
  Derived batch_expand(TorchShapeRef batch_size) const;
 
  BatchTensor base_expand(TorchShapeRef base_size) const;
 
  template <class Derived2>
  Derived batch_expand_as(const Derived2 & other) const;
 
  template <class Derived2>
  Derived2 base_expand_as(const Derived2 & other) const;
 
  Derived batch_expand_copy(TorchShapeRef batch_size) const;
 
  BatchTensor base_expand_copy(TorchShapeRef base_size) const;
 
  Derived batch_reshape(TorchShapeRef batch_shape) const;
 
  BatchTensor base_reshape(TorchShapeRef base_shape) const;
 
  Derived batch_unsqueeze(TorchSize d) const;
 
  Derived list_unsqueeze() const;
 
  BatchTensor base_unsqueeze(TorchSize d) const;
 
  Derived batch_transpose(TorchSize d1, TorchSize d2) const;
 
  BatchTensor base_transpose(TorchSize d1, TorchSize d2) const;
 
  BatchTensor base_movedim(TorchSize d1, TorchSize d2) const;
 
  Derived clone(torch::MemoryFormat memory_format = torch::MemoryFormat::Contiguous) const;
 
  Derived detach() const;
 
  Derived to(const torch::TensorOptions & options) const;
 
  Derived operator-() const;
 
  Derived batch_sum(TorchSize d) const;
 
  Derived list_sum() const;
 
private:
  TorchSize _batch_dim;
};
 
template <class Derived>
template <class Derived2>
Derived
BatchTensorBase<Derived>::batch_expand_as(const Derived2 & other) const
{
  return batch_expand(other.batch_sizes());
}
 
template <class Derived>
template <class Derived2>
Derived2
BatchTensorBase<Derived>::base_expand_as(const Derived2 & other) const
{
  return base_expand(other.base_sizes());
}
 
template <class Derived,
          typename = typename std::enable_if<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator+(const Derived & a, const Real & b)
{
  return Derived(torch::operator+(a, b), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator+(const Real & a, const Derived & b)
{
  return b + a;
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator+(const Derived & a, const Derived & b)
{
  neml_assert_broadcastable_dbg(a, b);
  return Derived(torch::operator+(a, b), broadcast_batch_dim(a, b));
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator-(const Derived & a, const Real & b)
{
  return Derived(torch::operator-(a, b), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator-(const Real & a, const Derived & b)
{
  return -b + a;
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator-(const Derived & a, const Derived & b)
{
  neml_assert_broadcastable_dbg(a, b);
  return Derived(torch::operator-(a, b), broadcast_batch_dim(a, b));
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator*(const Derived & a, const Real & b)
{
  return Derived(torch::operator*(a, b), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator*(const Real & a, const Derived & b)
{
  return b * a;
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator/(const Derived & a, const Real & b)
{
  return Derived(torch::operator/(a, b), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator/(const Real & a, const Derived & b)
{
  return Derived(torch::operator/(a, b), b.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
operator/(const Derived & a, const Derived & b)
{
  neml_assert_broadcastable_dbg(a, b);
  return Derived(torch::operator/(a, b), broadcast_batch_dim(a, b));
}
 
namespace math
{
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
pow(const Derived & a, const Real & n)
{
  return Derived(torch::pow(a, n), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
pow(const Real & a, const Derived & n)
{
  return Derived(torch::pow(a, n), n.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
pow(const Derived & a, const Derived & n)
{
  neml_assert_broadcastable_dbg(a, n);
  return Derived(torch::pow(a, n), broadcast_batch_dim(a, n));
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
sign(const Derived & a)
{
  return Derived(torch::sign(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
cosh(const Derived & a)
{
  return Derived(torch::cosh(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
sinh(const Derived & a)
{
  return Derived(torch::sinh(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
tanh(const Derived & a)
{
  return Derived(torch::tanh(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
where(const torch::Tensor & condition, const Derived & a, const Derived & b)
{
  neml_assert_broadcastable_dbg(a, b);
  return Derived(torch::where(condition, a, b), broadcast_batch_dim(a, b));
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
heaviside(const Derived & a)
{
  return (sign(a) + 1.0) / 2.0;
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
macaulay(const Derived & a)
{
  return Derived(torch::Tensor(a) * torch::Tensor(heaviside(a)), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
dmacaulay(const Derived & a)
{
  return heaviside(a);
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
sqrt(const Derived & a)
{
  return Derived(torch::sqrt(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
exp(const Derived & a)
{
  return Derived(torch::exp(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
abs(const Derived & a)
{
  return Derived(torch::abs(a), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
diff(const Derived & a, TorchSize n = 1, TorchSize dim = -1)
{
  return Derived(torch::diff(a, n, dim), a.batch_dim());
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
batch_diag_embed(const Derived & a, TorchSize offset = 0, TorchSize d1 = -2, TorchSize d2 = -1)
{
  return Derived(torch::diag_embed(
                     a, offset, d1 < 0 ? d1 - a.base_dim() : d1, d2 < 0 ? d2 - a.base_dim() : d2),
                 a.batch_dim() + 1);
}
 
template <
    class Derived,
    typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<Derived>, Derived>>>
Derived
log(const Derived & a)
{
  return Derived(torch::log(a), a.batch_dim());
}
 
} // namespace math
} // namespace neml2