variable_matrix.hpp

// Copyright (c) Sleipnir contributors
 
#pragma once
 
#include <algorithm>
#include <concepts>
#include <initializer_list>
#include <iterator>
#include <span>
#include <utility>
#include <vector>
 
#include <Eigen/Core>
 
#include "sleipnir/autodiff/slice.hpp"
#include "sleipnir/autodiff/variable.hpp"
#include "sleipnir/autodiff/variable_block.hpp"
#include "sleipnir/util/assert.hpp"
#include "sleipnir/util/concepts.hpp"
#include "sleipnir/util/function_ref.hpp"
#include "sleipnir/util/small_vector.hpp"
#include "sleipnir/util/symbol_exports.hpp"
 
namespace slp {
 
class SLEIPNIR_DLLEXPORT VariableMatrix {
 public:
  struct empty_t {};
 
  static constexpr empty_t empty{};
 
  VariableMatrix() = default;
 
  explicit VariableMatrix(int rows) : m_rows{rows}, m_cols{1} {
    m_storage.reserve(rows);
    for (int row = 0; row < rows; ++row) {
      m_storage.emplace_back();
    }
  }
 
  VariableMatrix(int rows, int cols) : m_rows{rows}, m_cols{cols} {
    m_storage.reserve(rows * cols);
    for (int index = 0; index < rows * cols; ++index) {
      m_storage.emplace_back();
    }
  }
 
  VariableMatrix(empty_t, int rows, int cols) : m_rows{rows}, m_cols{cols} {
    m_storage.reserve(rows * cols);
    for (int index = 0; index < rows * cols; ++index) {
      m_storage.emplace_back(nullptr);
    }
  }
 
  VariableMatrix(  // NOLINT
      std::initializer_list<std::initializer_list<Variable>> list) {
    // Get row and column counts for destination matrix
    m_rows = list.size();
    m_cols = 0;
    if (list.size() > 0) {
      m_cols = list.begin()->size();
    }
 
    // Assert the first and latest column counts are the same
    for ([[maybe_unused]]
         const auto& row : list) {
      slp_assert(list.begin()->size() == row.size());
    }
 
    m_storage.reserve(rows() * cols());
    for (const auto& row : list) {
      std::ranges::copy(row, std::back_inserter(m_storage));
    }
  }
 
  VariableMatrix(const std::vector<std::vector<double>>& list) {  // NOLINT
    // Get row and column counts for destination matrix
    m_rows = list.size();
    m_cols = 0;
    if (list.size() > 0) {
      m_cols = list.begin()->size();
    }
 
    // Assert the first and latest column counts are the same
    for ([[maybe_unused]]
         const auto& row : list) {
      slp_assert(list.begin()->size() == row.size());
    }
 
    m_storage.reserve(rows() * cols());
    for (const auto& row : list) {
      std::ranges::copy(row, std::back_inserter(m_storage));
    }
  }
 
  VariableMatrix(const std::vector<std::vector<Variable>>& list) {  // NOLINT
    // Get row and column counts for destination matrix
    m_rows = list.size();
    m_cols = 0;
    if (list.size() > 0) {
      m_cols = list.begin()->size();
    }
 
    // Assert the first and latest column counts are the same
    for ([[maybe_unused]]
         const auto& row : list) {
      slp_assert(list.begin()->size() == row.size());
    }
 
    m_storage.reserve(rows() * cols());
    for (const auto& row : list) {
      std::ranges::copy(row, std::back_inserter(m_storage));
    }
  }
 
  template <typename Derived>
  VariableMatrix(const Eigen::MatrixBase<Derived>& values)  // NOLINT
      : m_rows{static_cast<int>(values.rows())},
        m_cols{static_cast<int>(values.cols())} {
    m_storage.reserve(values.rows() * values.cols());
    for (int row = 0; row < values.rows(); ++row) {
      for (int col = 0; col < values.cols(); ++col) {
        m_storage.emplace_back(values(row, col));
      }
    }
  }
 
  template <typename Derived>
  VariableMatrix(const Eigen::DiagonalBase<Derived>& values)  // NOLINT
      : m_rows{static_cast<int>(values.rows())},
        m_cols{static_cast<int>(values.cols())} {
    m_storage.reserve(values.rows() * values.cols());
    for (int row = 0; row < values.rows(); ++row) {
      for (int col = 0; col < values.cols(); ++col) {
        if (row == col) {
          m_storage.emplace_back(values.diagonal()[row]);
        } else {
          m_storage.emplace_back(0.0);
        }
      }
    }
  }
 
  template <typename Derived>
  VariableMatrix& operator=(const Eigen::MatrixBase<Derived>& values) {
    slp_assert(rows() == values.rows() && cols() == values.cols());
 
    for (int row = 0; row < values.rows(); ++row) {
      for (int col = 0; col < values.cols(); ++col) {
        (*this)[row, col] = values(row, col);
      }
    }
 
    return *this;
  }
 
  VariableMatrix& operator=(ScalarLike auto value) {
    slp_assert(rows() == 1 && cols() == 1);
 
    (*this)[0, 0] = value;
 
    return *this;
  }
 
  template <typename Derived>
    requires std::same_as<typename Derived::Scalar, double>
  void set_value(const Eigen::MatrixBase<Derived>& values) {
    slp_assert(rows() == values.rows() && cols() == values.cols());
 
    for (int row = 0; row < values.rows(); ++row) {
      for (int col = 0; col < values.cols(); ++col) {
        (*this)[row, col].set_value(values(row, col));
      }
    }
  }
 
  VariableMatrix(const Variable& variable)  // NOLINT
      : m_rows{1}, m_cols{1} {
    m_storage.emplace_back(variable);
  }
 
  VariableMatrix(Variable&& variable) : m_rows{1}, m_cols{1} {  // NOLINT
    m_storage.emplace_back(std::move(variable));
  }
 
  VariableMatrix(const VariableBlock<VariableMatrix>& values)  // NOLINT
      : m_rows{values.rows()}, m_cols{values.cols()} {
    m_storage.reserve(rows() * cols());
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        m_storage.emplace_back(values[row, col]);
      }
    }
  }
 
  VariableMatrix(const VariableBlock<const VariableMatrix>& values)  // NOLINT
      : m_rows{values.rows()}, m_cols{values.cols()} {
    m_storage.reserve(rows() * cols());
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        m_storage.emplace_back(values[row, col]);
      }
    }
  }
 
  explicit VariableMatrix(std::span<const Variable> values)
      : m_rows{static_cast<int>(values.size())}, m_cols{1} {
    m_storage.reserve(rows() * cols());
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        m_storage.emplace_back(values[row * cols() + col]);
      }
    }
  }
 
  VariableMatrix(std::span<const Variable> values, int rows, int cols)
      : m_rows{rows}, m_cols{cols} {
    slp_assert(static_cast<int>(values.size()) == rows * cols);
    m_storage.reserve(rows * cols);
    for (int row = 0; row < rows; ++row) {
      for (int col = 0; col < cols; ++col) {
        m_storage.emplace_back(values[row * cols + col]);
      }
    }
  }
 
  Variable& operator[](int row, int col) {
    slp_assert(row >= 0 && row < rows());
    slp_assert(col >= 0 && col < cols());
    return m_storage[row * cols() + col];
  }
 
  const Variable& operator[](int row, int col) const {
    slp_assert(row >= 0 && row < rows());
    slp_assert(col >= 0 && col < cols());
    return m_storage[row * cols() + col];
  }
 
  Variable& operator[](int row) {
    slp_assert(row >= 0 && row < rows() * cols());
    return m_storage[row];
  }
 
  const Variable& operator[](int row) const {
    slp_assert(row >= 0 && row < rows() * cols());
    return m_storage[row];
  }
 
  VariableBlock<VariableMatrix> block(int row_offset, int col_offset,
                                      int block_rows, int block_cols) {
    slp_assert(row_offset >= 0 && row_offset <= rows());
    slp_assert(col_offset >= 0 && col_offset <= cols());
    slp_assert(block_rows >= 0 && block_rows <= rows() - row_offset);
    slp_assert(block_cols >= 0 && block_cols <= cols() - col_offset);
    return VariableBlock{*this, row_offset, col_offset, block_rows, block_cols};
  }
 
  const VariableBlock<const VariableMatrix> block(int row_offset,
                                                  int col_offset,
                                                  int block_rows,
                                                  int block_cols) const {
    slp_assert(row_offset >= 0 && row_offset <= rows());
    slp_assert(col_offset >= 0 && col_offset <= cols());
    slp_assert(block_rows >= 0 && block_rows <= rows() - row_offset);
    slp_assert(block_cols >= 0 && block_cols <= cols() - col_offset);
    return VariableBlock{*this, row_offset, col_offset, block_rows, block_cols};
  }
 
  VariableBlock<VariableMatrix> operator[](Slice row_slice, Slice col_slice) {
    int row_slice_length = row_slice.adjust(rows());
    int col_slice_length = col_slice.adjust(cols());
    return VariableBlock{*this, std::move(row_slice), row_slice_length,
                         std::move(col_slice), col_slice_length};
  }
 
  const VariableBlock<const VariableMatrix> operator[](Slice row_slice,
                                                       Slice col_slice) const {
    int row_slice_length = row_slice.adjust(rows());
    int col_slice_length = col_slice.adjust(cols());
    return VariableBlock{*this, std::move(row_slice), row_slice_length,
                         std::move(col_slice), col_slice_length};
  }
 
  VariableBlock<VariableMatrix> operator[](Slice row_slice,
                                           int row_slice_length,
                                           Slice col_slice,
                                           int col_slice_length) {
    return VariableBlock{*this, std::move(row_slice), row_slice_length,
                         std::move(col_slice), col_slice_length};
  }
 
  const VariableBlock<const VariableMatrix> operator[](
      Slice row_slice, int row_slice_length, Slice col_slice,
      int col_slice_length) const {
    return VariableBlock{*this, std::move(row_slice), row_slice_length,
                         std::move(col_slice), col_slice_length};
  }
 
  VariableBlock<VariableMatrix> segment(int offset, int length) {
    slp_assert(offset >= 0 && offset < rows() * cols());
    slp_assert(length >= 0 && length <= rows() * cols() - offset);
    return block(offset, 0, length, 1);
  }
 
  const VariableBlock<const VariableMatrix> segment(int offset,
                                                    int length) const {
    slp_assert(offset >= 0 && offset < rows() * cols());
    slp_assert(length >= 0 && length <= rows() * cols() - offset);
    return block(offset, 0, length, 1);
  }
 
  VariableBlock<VariableMatrix> row(int row) {
    slp_assert(row >= 0 && row < rows());
    return block(row, 0, 1, cols());
  }
 
  const VariableBlock<const VariableMatrix> row(int row) const {
    slp_assert(row >= 0 && row < rows());
    return block(row, 0, 1, cols());
  }
 
  VariableBlock<VariableMatrix> col(int col) {
    slp_assert(col >= 0 && col < cols());
    return block(0, col, rows(), 1);
  }
 
  const VariableBlock<const VariableMatrix> col(int col) const {
    slp_assert(col >= 0 && col < cols());
    return block(0, col, rows(), 1);
  }
 
  template <MatrixLike LHS, MatrixLike RHS>
    requires SleipnirMatrixLike<LHS> || SleipnirMatrixLike<RHS>
  friend SLEIPNIR_DLLEXPORT VariableMatrix operator*(const LHS& lhs,
                                                     const RHS& rhs) {
    slp_assert(lhs.cols() == rhs.rows());
 
    VariableMatrix result(VariableMatrix::empty, lhs.rows(), rhs.cols());
 
    for (int i = 0; i < lhs.rows(); ++i) {
      for (int j = 0; j < rhs.cols(); ++j) {
        Variable sum;
        for (int k = 0; k < lhs.cols(); ++k) {
          if constexpr (SleipnirMatrixLike<LHS> && SleipnirMatrixLike<RHS>) {
            sum += lhs[i, k] * rhs[k, j];
          } else if constexpr (SleipnirMatrixLike<LHS> &&
                               EigenMatrixLike<RHS>) {
            sum += lhs[i, k] * rhs(k, j);
          } else if constexpr (EigenMatrixLike<LHS> &&
                               SleipnirMatrixLike<RHS>) {
            sum += lhs(i, k) * rhs[k, j];
          }
        }
        result[i, j] = sum;
      }
    }
 
    return result;
  }
 
  friend SLEIPNIR_DLLEXPORT VariableMatrix
  operator*(const SleipnirMatrixLike auto& lhs, const ScalarLike auto& rhs) {
    VariableMatrix result{VariableMatrix::empty, lhs.rows(), lhs.cols()};
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        result[row, col] = lhs[row, col] * rhs;
      }
    }
 
    return result;
  }
 
  friend SLEIPNIR_DLLEXPORT VariableMatrix operator*(const MatrixLike auto& lhs,
                                                     const Variable& rhs) {
    VariableMatrix result(VariableMatrix::empty, lhs.rows(), lhs.cols());
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        if constexpr (SleipnirMatrixLike<decltype(lhs)>) {
          result[row, col] = lhs[row, col] * rhs;
        } else {
          result[row, col] = lhs(row, col) * rhs;
        }
      }
    }
 
    return result;
  }
 
  friend SLEIPNIR_DLLEXPORT VariableMatrix
  operator*(const ScalarLike auto& lhs, const SleipnirMatrixLike auto& rhs) {
    VariableMatrix result{VariableMatrix::empty, rhs.rows(), rhs.cols()};
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        result[row, col] = rhs[row, col] * lhs;
      }
    }
 
    return result;
  }
 
  friend SLEIPNIR_DLLEXPORT VariableMatrix
  operator*(const Variable& lhs, const MatrixLike auto& rhs) {
    VariableMatrix result(VariableMatrix::empty, rhs.rows(), rhs.cols());
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        if constexpr (SleipnirMatrixLike<decltype(rhs)>) {
          result[row, col] = rhs[row, col] * lhs;
        } else {
          result[row, col] = rhs(row, col) * lhs;
        }
      }
    }
 
    return result;
  }
 
  VariableMatrix& operator*=(const MatrixLike auto& rhs) {
    slp_assert(cols() == rhs.rows() && cols() == rhs.cols());
 
    for (int i = 0; i < rows(); ++i) {
      for (int j = 0; j < rhs.cols(); ++j) {
        Variable sum;
        for (int k = 0; k < cols(); ++k) {
          if constexpr (SleipnirMatrixLike<decltype(rhs)>) {
            sum += (*this)[i, k] * rhs[k, j];
          } else {
            sum += (*this)[i, k] * rhs(k, j);
          }
        }
        (*this)[i, j] = sum;
      }
    }
 
    return *this;
  }
 
  VariableMatrix& operator*=(const ScalarLike auto& rhs) {
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < rhs.cols(); ++col) {
        (*this)[row, col] *= rhs;
      }
    }
 
    return *this;
  }
 
  friend SLEIPNIR_DLLEXPORT VariableMatrix
  operator/(const MatrixLike auto& lhs, const ScalarLike auto& rhs) {
    VariableMatrix result(VariableMatrix::empty, lhs.rows(), lhs.cols());
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        if constexpr (SleipnirMatrixLike<decltype(lhs)>) {
          result[row, col] = lhs[row, col] / rhs;
        } else {
          result[row, col] = lhs(row, col) / rhs;
        }
      }
    }
 
    return result;
  }
 
  VariableMatrix& operator/=(const ScalarLike auto& rhs) {
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        (*this)[row, col] /= rhs;
      }
    }
 
    return *this;
  }
 
  template <MatrixLike LHS, MatrixLike RHS>
    requires SleipnirMatrixLike<LHS> || SleipnirMatrixLike<RHS>
  friend SLEIPNIR_DLLEXPORT VariableMatrix operator+(const LHS& lhs,
                                                     const RHS& rhs) {
    slp_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
 
    VariableMatrix result(VariableMatrix::empty, lhs.rows(), lhs.cols());
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        if constexpr (SleipnirMatrixLike<LHS> && SleipnirMatrixLike<RHS>) {
          result[row, col] = lhs[row, col] + rhs[row, col];
        } else if constexpr (SleipnirMatrixLike<LHS> && EigenMatrixLike<RHS>) {
          result[row, col] = lhs[row, col] + rhs(row, col);
        } else if constexpr (EigenMatrixLike<LHS> && SleipnirMatrixLike<RHS>) {
          result[row, col] = lhs(row, col) + rhs[row, col];
        }
      }
    }
 
    return result;
  }
 
  VariableMatrix& operator+=(const MatrixLike auto& rhs) {
    slp_assert(rows() == rhs.rows() && cols() == rhs.cols());
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        if constexpr (SleipnirMatrixLike<decltype(rhs)>) {
          (*this)[row, col] += rhs[row, col];
        } else {
          (*this)[row, col] += rhs(row, col);
        }
      }
    }
 
    return *this;
  }
 
  VariableMatrix& operator+=(const ScalarLike auto& rhs) {
    slp_assert(rows() == 1 && cols() == 1);
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        (*this)[row, col] += rhs;
      }
    }
 
    return *this;
  }
 
  template <MatrixLike LHS, MatrixLike RHS>
    requires SleipnirMatrixLike<LHS> || SleipnirMatrixLike<RHS>
  friend SLEIPNIR_DLLEXPORT VariableMatrix operator-(const LHS& lhs,
                                                     const RHS& rhs) {
    slp_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
 
    VariableMatrix result(VariableMatrix::empty, lhs.rows(), lhs.cols());
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        if constexpr (SleipnirMatrixLike<LHS> && SleipnirMatrixLike<RHS>) {
          result[row, col] = lhs[row, col] - rhs[row, col];
        } else if constexpr (SleipnirMatrixLike<LHS> && EigenMatrixLike<RHS>) {
          result[row, col] = lhs[row, col] - rhs(row, col);
        } else if constexpr (EigenMatrixLike<LHS> && SleipnirMatrixLike<RHS>) {
          result[row, col] = lhs(row, col) - rhs[row, col];
        }
      }
    }
 
    return result;
  }
 
  VariableMatrix& operator-=(const MatrixLike auto& rhs) {
    slp_assert(rows() == rhs.rows() && cols() == rhs.cols());
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        if constexpr (SleipnirMatrixLike<decltype(rhs)>) {
          (*this)[row, col] -= rhs[row, col];
        } else {
          (*this)[row, col] -= rhs(row, col);
        }
      }
    }
 
    return *this;
  }
 
  VariableMatrix& operator-=(const ScalarLike auto& rhs) {
    slp_assert(rows() == 1 && cols() == 1);
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        (*this)[row, col] -= rhs;
      }
    }
 
    return *this;
  }
 
  friend SLEIPNIR_DLLEXPORT VariableMatrix
  operator-(const SleipnirMatrixLike auto& lhs) {
    VariableMatrix result{VariableMatrix::empty, lhs.rows(), lhs.cols()};
 
    for (int row = 0; row < result.rows(); ++row) {
      for (int col = 0; col < result.cols(); ++col) {
        result[row, col] = -lhs[row, col];
      }
    }
 
    return result;
  }
 
  operator Variable() const {  // NOLINT
    slp_assert(rows() == 1 && cols() == 1);
    return (*this)[0, 0];
  }
 
  VariableMatrix T() const {
    VariableMatrix result{VariableMatrix::empty, cols(), rows()};
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        result[col, row] = (*this)[row, col];
      }
    }
 
    return result;
  }
 
  int rows() const { return m_rows; }
 
  int cols() const { return m_cols; }
 
  double value(int row, int col) {
    slp_assert(row >= 0 && row < rows());
    slp_assert(col >= 0 && col < cols());
    return m_storage[row * cols() + col].value();
  }
 
  double value(int index) {
    slp_assert(index >= 0 && index < rows() * cols());
    return m_storage[index].value();
  }
 
  Eigen::MatrixXd value() {
    Eigen::MatrixXd result{rows(), cols()};
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        result(row, col) = value(row, col);
      }
    }
 
    return result;
  }
 
  VariableMatrix cwise_transform(
      function_ref<Variable(const Variable& x)> unary_op) const {
    VariableMatrix result{VariableMatrix::empty, rows(), cols()};
 
    for (int row = 0; row < rows(); ++row) {
      for (int col = 0; col < cols(); ++col) {
        result[row, col] = unary_op((*this)[row, col]);
      }
    }
 
    return result;
  }
 
#ifndef DOXYGEN_SHOULD_SKIP_THIS
 
  class iterator {
   public:
    using iterator_category = std::forward_iterator_tag;
    using value_type = Variable;
    using difference_type = std::ptrdiff_t;
    using pointer = Variable*;
    using reference = Variable&;
 
    constexpr iterator() noexcept = default;
 
    explicit constexpr iterator(small_vector<Variable>::iterator it) noexcept
        : m_it{it} {}
 
    constexpr iterator& operator++() noexcept {
      ++m_it;
      return *this;
    }
 
    constexpr iterator operator++(int) noexcept {
      iterator retval = *this;
      ++(*this);
      return retval;
    }
 
    constexpr bool operator==(const iterator&) const noexcept = default;
 
    constexpr reference operator*() const noexcept { return *m_it; }
 
   private:
    small_vector<Variable>::iterator m_it;
  };
 
  class const_iterator {
   public:
    using iterator_category = std::forward_iterator_tag;
    using value_type = Variable;
    using difference_type = std::ptrdiff_t;
    using pointer = Variable*;
    using const_reference = const Variable&;
 
    constexpr const_iterator() noexcept = default;
 
    explicit constexpr const_iterator(
        small_vector<Variable>::const_iterator it) noexcept
        : m_it{it} {}
 
    constexpr const_iterator& operator++() noexcept {
      ++m_it;
      return *this;
    }
 
    constexpr const_iterator operator++(int) noexcept {
      const_iterator retval = *this;
      ++(*this);
      return retval;
    }
 
    constexpr bool operator==(const const_iterator&) const noexcept = default;
 
    constexpr const_reference operator*() const noexcept { return *m_it; }
 
   private:
    small_vector<Variable>::const_iterator m_it;
  };
 
#endif  // DOXYGEN_SHOULD_SKIP_THIS
 
  iterator begin() { return iterator{m_storage.begin()}; }
 
  iterator end() { return iterator{m_storage.end()}; }
 
  const_iterator begin() const { return const_iterator{m_storage.begin()}; }
 
  const_iterator end() const { return const_iterator{m_storage.end()}; }
 
  const_iterator cbegin() const { return const_iterator{m_storage.cbegin()}; }
 
  const_iterator cend() const { return const_iterator{m_storage.cend()}; }
 
  size_t size() const { return m_storage.size(); }
 
  static VariableMatrix zero(int rows, int cols) {
    VariableMatrix result{VariableMatrix::empty, rows, cols};
 
    for (auto& elem : result) {
      elem = 0.0;
    }
 
    return result;
  }
 
  static VariableMatrix ones(int rows, int cols) {
    VariableMatrix result{VariableMatrix::empty, rows, cols};
 
    for (auto& elem : result) {
      elem = 1.0;
    }
 
    return result;
  }
 
 private:
  small_vector<Variable> m_storage;
  int m_rows = 0;
  int m_cols = 0;
};
 
SLEIPNIR_DLLEXPORT inline VariableMatrix cwise_reduce(
    const VariableMatrix& lhs, const VariableMatrix& rhs,
    function_ref<Variable(const Variable& x, const Variable& y)> binary_op) {
  slp_assert(lhs.rows() == rhs.rows() && lhs.rows() == rhs.rows());
 
  VariableMatrix result{VariableMatrix::empty, lhs.rows(), lhs.cols()};
 
  for (int row = 0; row < lhs.rows(); ++row) {
    for (int col = 0; col < lhs.cols(); ++col) {
      result[row, col] = binary_op(lhs[row, col], rhs[row, col]);
    }
  }
 
  return result;
}
 
SLEIPNIR_DLLEXPORT inline VariableMatrix block(
    std::initializer_list<std::initializer_list<VariableMatrix>> list) {
  // Get row and column counts for destination matrix
  int rows = 0;
  int cols = -1;
  for (const auto& row : list) {
    if (row.size() > 0) {
      rows += row.begin()->rows();
    }
 
    // Get number of columns in this row
    int latest_cols = 0;
    for (const auto& elem : row) {
      // Assert the first and latest row have the same height
      slp_assert(row.begin()->rows() == elem.rows());
 
      latest_cols += elem.cols();
    }
 
    // If this is the first row, record the column count. Otherwise, assert the
    // first and latest column counts are the same.
    if (cols == -1) {
      cols = latest_cols;
    } else {
      slp_assert(cols == latest_cols);
    }
  }
 
  VariableMatrix result{VariableMatrix::empty, rows, cols};
 
  int row_offset = 0;
  for (const auto& row : list) {
    int col_offset = 0;
    for (const auto& elem : row) {
      result.block(row_offset, col_offset, elem.rows(), elem.cols()) = elem;
      col_offset += elem.cols();
    }
    row_offset += row.begin()->rows();
  }
 
  return result;
}
 
SLEIPNIR_DLLEXPORT inline VariableMatrix block(
    const std::vector<std::vector<VariableMatrix>>& list) {
  // Get row and column counts for destination matrix
  int rows = 0;
  int cols = -1;
  for (const auto& row : list) {
    if (row.size() > 0) {
      rows += row.begin()->rows();
    }
 
    // Get number of columns in this row
    int latest_cols = 0;
    for (const auto& elem : row) {
      // Assert the first and latest row have the same height
      slp_assert(row.begin()->rows() == elem.rows());
 
      latest_cols += elem.cols();
    }
 
    // If this is the first row, record the column count. Otherwise, assert the
    // first and latest column counts are the same.
    if (cols == -1) {
      cols = latest_cols;
    } else {
      slp_assert(cols == latest_cols);
    }
  }
 
  VariableMatrix result{VariableMatrix::empty, rows, cols};
 
  int row_offset = 0;
  for (const auto& row : list) {
    int col_offset = 0;
    for (const auto& elem : row) {
      result.block(row_offset, col_offset, elem.rows(), elem.cols()) = elem;
      col_offset += elem.cols();
    }
    row_offset += row.begin()->rows();
  }
 
  return result;
}
 
SLEIPNIR_DLLEXPORT VariableMatrix solve(const VariableMatrix& A,
                                        const VariableMatrix& B);
 
}  // namespace slp