diff --git a/internal/ceres/compressed_row_sparse_matrix.cc b/internal/ceres/compressed_row_sparse_matrix.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/compressed_row_sparse_matrix.h"
+
+#include <algorithm>
+#include <vector>
+#include "ceres/matrix_proto.h"
+#include "ceres/internal/port.h"
+
+namespace ceres {
+namespace internal {
+namespace {
+
+// Helper functor used by the constructor for reordering the contents
+// of a TripletSparseMatrix.
+struct RowColLessThan {
+  RowColLessThan(const int* rows, const int* cols)
+      : rows(rows), cols(cols) {
+  }
+
+  bool operator()(const int x, const int y) const {
+    if (rows[x] == rows[y]) {
+      return (cols[x] < cols[y]);
+    }
+    return (rows[x] < rows[y]);
+  }
+
+  const int* rows;
+  const int* cols;
+};
+
+}  // namespace
+
+// This constructor gives you a semi-initialized CompressedRowSparseMatrix.
+CompressedRowSparseMatrix::CompressedRowSparseMatrix(int num_rows,
+                                                     int num_cols,
+                                                     int max_num_nonzeros) {
+  num_rows_ = num_rows;
+  num_cols_ = num_cols;
+  max_num_nonzeros_ = max_num_nonzeros;
+
+  VLOG(1) << "# of rows: " << num_rows_ << " # of columns: " << num_cols_
+          << " max_num_nonzeros: " << max_num_nonzeros_
+          << ". Allocating " << (num_rows_ + 1) * sizeof(int) +  // NOLINT
+      max_num_nonzeros_ * sizeof(int) +  // NOLINT
+      max_num_nonzeros_ * sizeof(double);  // NOLINT
+
+  rows_.reset(new int[num_rows_ + 1]);
+  cols_.reset(new int[max_num_nonzeros_]);
+  values_.reset(new double[max_num_nonzeros_]);
+
+  fill(rows_.get(), rows_.get() + num_rows_ + 1, 0);
+  fill(cols_.get(), cols_.get() + max_num_nonzeros_, 0);
+  fill(values_.get(), values_.get() + max_num_nonzeros_, 0);
+}
+
+CompressedRowSparseMatrix::CompressedRowSparseMatrix(
+    const TripletSparseMatrix& m) {
+  num_rows_ = m.num_rows();
+  num_cols_ = m.num_cols();
+  max_num_nonzeros_ = m.max_num_nonzeros();
+
+  // index is the list of indices into the TripletSparseMatrix m.
+  vector<int> index(m.num_nonzeros(), 0);
+  for (int i = 0; i < m.num_nonzeros(); ++i) {
+    index[i] = i;
+  }
+
+  // Sort index such that the entries of m are ordered by row and ties
+  // are broken by column.
+  sort(index.begin(), index.end(), RowColLessThan(m.rows(), m.cols()));
+
+  VLOG(1) << "# of rows: " << num_rows_ << " # of columns: " << num_cols_
+          << " max_num_nonzeros: " << max_num_nonzeros_
+          << ". Allocating " << (num_rows_ + 1) * sizeof(int) +  // NOLINT
+      max_num_nonzeros_ * sizeof(int) +  // NOLINT
+      max_num_nonzeros_ * sizeof(double);  // NOLINT
+
+  rows_.reset(new int[num_rows_ + 1]);
+  cols_.reset(new int[max_num_nonzeros_]);
+  values_.reset(new double[max_num_nonzeros_]);
+
+  // rows_ = 0
+  fill(rows_.get(), rows_.get() + num_rows_ + 1, 0);
+
+  // Copy the contents of the cols and values array in the order given
+  // by index and count the number of entries in each row.
+  for (int i = 0; i < m.num_nonzeros(); ++i) {
+    const int idx = index[i];
+    ++rows_[m.rows()[idx] + 1];
+    cols_[i] = m.cols()[idx];
+    values_[i] = m.values()[idx];
+  }
+
+  // Find the cumulative sum of the row counts.
+  for (int i = 1; i < num_rows_ + 1; ++i) {
+    rows_[i] += rows_[i-1];
+  }
+
+  CHECK_EQ(num_nonzeros(), m.num_nonzeros());
+}
+
+#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+CompressedRowSparseMatrix::CompressedRowSparseMatrix(
+    const SparseMatrixProto& outer_proto) {
+  CHECK(outer_proto.has_compressed_row_matrix());
+
+  const CompressedRowSparseMatrixProto& proto =
+      outer_proto.compressed_row_matrix();
+
+  num_rows_ = proto.num_rows();
+  num_cols_ = proto.num_cols();
+
+  rows_.reset(new int[proto.rows_size()]);
+  cols_.reset(new int[proto.cols_size()]);
+  values_.reset(new double[proto.values_size()]);
+
+  for (int i = 0; i < proto.rows_size(); ++i) {
+    rows_[i] = proto.rows(i);
+  }
+
+  CHECK_EQ(proto.rows_size(), num_rows_ + 1);
+  CHECK_EQ(proto.cols_size(), proto.values_size());
+  CHECK_EQ(proto.cols_size(), rows_[num_rows_]);
+
+  for (int i = 0; i < proto.cols_size(); ++i) {
+    cols_[i] = proto.cols(i);
+    values_[i] = proto.values(i);
+  }
+
+  max_num_nonzeros_ = proto.cols_size();
+}
+#endif
+
+CompressedRowSparseMatrix::CompressedRowSparseMatrix(const double* diagonal,
+                                                     int num_rows) {
+  CHECK_NOTNULL(diagonal);
+
+  num_rows_ = num_rows;
+  num_cols_ = num_rows;
+  max_num_nonzeros_ = num_rows;
+
+  rows_.reset(new int[num_rows_ + 1]);
+  cols_.reset(new int[num_rows_]);
+  values_.reset(new double[num_rows_]);
+
+  rows_[0] = 0;
+  for (int i = 0; i < num_rows_; ++i) {
+    cols_[i] = i;
+    values_[i] = diagonal[i];
+    rows_[i + 1] = i + 1;
+  }
+
+  CHECK_EQ(num_nonzeros(), num_rows);
+}
+
+CompressedRowSparseMatrix::~CompressedRowSparseMatrix() {
+}
+
+void CompressedRowSparseMatrix::SetZero() {
+  fill(values_.get(), values_.get() + num_nonzeros(), 0.0);
+}
+
+void CompressedRowSparseMatrix::RightMultiply(const double* x,
+                                              double* y) const {
+  CHECK_NOTNULL(x);
+  CHECK_NOTNULL(y);
+
+  for (int r = 0; r < num_rows_; ++r) {
+    for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
+      y[r] += values_[idx] * x[cols_[idx]];
+    }
+  }
+}
+
+void CompressedRowSparseMatrix::LeftMultiply(const double* x, double* y) const {
+  CHECK_NOTNULL(x);
+  CHECK_NOTNULL(y);
+
+  for (int r = 0; r < num_rows_; ++r) {
+    for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
+      y[cols_[idx]] += values_[idx] * x[r];
+    }
+  }
+}
+
+void CompressedRowSparseMatrix::SquaredColumnNorm(double* x) const {
+  CHECK_NOTNULL(x);
+
+  fill(x, x + num_cols_, 0.0);
+  for (int idx = 0; idx < rows_[num_rows_]; ++idx) {
+    x[cols_[idx]] += values_[idx] * values_[idx];
+  }
+}
+
+void CompressedRowSparseMatrix::ScaleColumns(const double* scale) {
+  CHECK_NOTNULL(scale);
+
+  for (int idx = 0; idx < rows_[num_rows_]; ++idx) {
+    values_[idx] *= scale[cols_[idx]];
+  }
+}
+
+void CompressedRowSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
+  CHECK_NOTNULL(dense_matrix);
+  dense_matrix->resize(num_rows_, num_cols_);
+  dense_matrix->setZero();
+
+  for (int r = 0; r < num_rows_; ++r) {
+    for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
+      (*dense_matrix)(r, cols_[idx]) = values_[idx];
+    }
+  }
+}
+
+#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+void CompressedRowSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
+  CHECK_NOTNULL(outer_proto);
+
+  outer_proto->Clear();
+  CompressedRowSparseMatrixProto* proto
+      = outer_proto->mutable_compressed_row_matrix();
+
+  proto->set_num_rows(num_rows_);
+  proto->set_num_cols(num_cols_);
+
+  for (int r = 0; r < num_rows_ + 1; ++r) {
+    proto->add_rows(rows_[r]);
+  }
+
+  for (int idx = 0; idx < rows_[num_rows_]; ++idx) {
+    proto->add_cols(cols_[idx]);
+    proto->add_values(values_[idx]);
+  }
+}
+#endif
+
+void CompressedRowSparseMatrix::DeleteRows(int delta_rows) {
+  CHECK_GE(delta_rows, 0);
+  CHECK_LE(delta_rows, num_rows_);
+
+  int new_num_rows = num_rows_ - delta_rows;
+
+  num_rows_ = new_num_rows;
+  int* new_rows = new int[num_rows_ + 1];
+  copy(rows_.get(), rows_.get() + num_rows_ + 1, new_rows);
+  rows_.reset(new_rows);
+}
+
+void CompressedRowSparseMatrix::AppendRows(const CompressedRowSparseMatrix& m) {
+  CHECK_EQ(m.num_cols(), num_cols_);
+
+  // Check if there is enough space. If not, then allocate new arrays
+  // to hold the combined matrix and copy the contents of this matrix
+  // into it.
+  if (max_num_nonzeros_ < num_nonzeros() + m.num_nonzeros()) {
+    int new_max_num_nonzeros =  num_nonzeros() + m.num_nonzeros();
+
+    VLOG(1) << "Reallocating " << sizeof(int) * new_max_num_nonzeros;  // NOLINT
+
+    int* new_cols = new int[new_max_num_nonzeros];
+    copy(cols_.get(), cols_.get() + max_num_nonzeros_, new_cols);
+    cols_.reset(new_cols);
+
+    double* new_values = new double[new_max_num_nonzeros];
+    copy(values_.get(), values_.get() + max_num_nonzeros_, new_values);
+    values_.reset(new_values);
+
+    max_num_nonzeros_ = new_max_num_nonzeros;
+  }
+
+  // Copy the contents of m into this matrix.
+  copy(m.cols(), m.cols() + m.num_nonzeros(), cols_.get() + num_nonzeros());
+  copy(m.values(),
+       m.values() + m.num_nonzeros(),
+       values_.get() + num_nonzeros());
+
+  // Create the new rows array to hold the enlarged matrix.
+  int* new_rows = new int[num_rows_ + m.num_rows() + 1];
+  // The first num_rows_ entries are the same
+  copy(rows_.get(), rows_.get() + num_rows_, new_rows);
+
+  // new_rows = [rows_, m.row() + rows_[num_rows_]]
+  fill(new_rows + num_rows_,
+       new_rows + num_rows_ + m.num_rows() + 1,
+       rows_[num_rows_]);
+
+  for (int r = 0; r < m.num_rows() + 1; ++r) {
+    new_rows[num_rows_ + r] += m.rows()[r];
+  }
+
+  rows_.reset(new_rows);
+  num_rows_ += m.num_rows();
+}
+
+}  // namespace internal
+}  // namespace ceres