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diff --git a/internal/ceres/block_jacobi_preconditioner.cc b/internal/ceres/block_jacobi_preconditioner.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 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: keir@google.com (Keir Mierle)
+
+#include "ceres/block_jacobi_preconditioner.h"
+
+#include "Eigen/Cholesky"
+#include "ceres/block_sparse_matrix.h"
+#include "ceres/block_structure.h"
+#include "ceres/casts.h"
+#include "ceres/integral_types.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+BlockJacobiPreconditioner::BlockJacobiPreconditioner(const LinearOperator& A)
+    : num_rows_(A.num_rows()),
+      block_structure_(
+        *(down_cast<const BlockSparseMatrix*>(&A)->block_structure())) {
+  // Calculate the amount of storage needed.
+  int storage_needed = 0;
+  for (int c = 0; c < block_structure_.cols.size(); ++c) {
+    int size = block_structure_.cols[c].size;
+    storage_needed += size * size;
+  }
+
+  // Size the offsets and storage.
+  blocks_.resize(block_structure_.cols.size());
+  block_storage_.resize(storage_needed);
+
+  // Put pointers to the storage in the offsets.
+  double* block_cursor = &block_storage_[0];
+  for (int c = 0; c < block_structure_.cols.size(); ++c) {
+    int size = block_structure_.cols[c].size;
+    blocks_[c] = block_cursor;
+    block_cursor += size * size;
+  }
+}
+
+BlockJacobiPreconditioner::~BlockJacobiPreconditioner() {
+}
+
+void BlockJacobiPreconditioner::Update(const LinearOperator& matrix, const double* D) {
+  const BlockSparseMatrix& A = *(down_cast<const BlockSparseMatrix*>(&matrix));
+  const CompressedRowBlockStructure* bs = A.block_structure();
+
+  // Compute the diagonal blocks by block inner products.
+  std::fill(block_storage_.begin(), block_storage_.end(), 0.0);
+  for (int r = 0; r < bs->rows.size(); ++r) {
+    const int row_block_size = bs->rows[r].block.size;
+    const vector<Cell>& cells = bs->rows[r].cells;
+    const double* row_values = A.RowBlockValues(r);
+    for (int c = 0; c < cells.size(); ++c) {
+      const int col_block_size = bs->cols[cells[c].block_id].size;
+      ConstMatrixRef m(row_values + cells[c].position,
+                       row_block_size,
+                       col_block_size);
+
+      MatrixRef(blocks_[cells[c].block_id],
+                col_block_size,
+                col_block_size).noalias() += m.transpose() * m;
+
+      // TODO(keir): Figure out when the below expression is actually faster
+      // than doing the full rank update. The issue is that for smaller sizes,
+      // the rankUpdate() function is slower than the full product done above.
+      //
+      // On the typical bundling problems, the above product is ~5% faster.
+      //
+      //   MatrixRef(blocks_[cells[c].block_id],
+      //             col_block_size,
+      //             col_block_size).selfadjointView<Eigen::Upper>().rankUpdate(m);
+      //
+    }
+  }
+
+  // Add the diagonal and invert each block.
+  for (int c = 0; c < bs->cols.size(); ++c) {
+    const int size = block_structure_.cols[c].size;
+    const int position = block_structure_.cols[c].position;
+    MatrixRef block(blocks_[c], size, size);
+
+    if (D != NULL) {
+      block.diagonal() += ConstVectorRef(D + position, size).array().square().matrix();
+    }
+
+    block = block.selfadjointView<Eigen::Upper>()
+                 .ldlt()
+                 .solve(Matrix::Identity(size, size));
+  }
+}
+
+void BlockJacobiPreconditioner::RightMultiply(const double* x, double* y) const {
+  for (int c = 0; c < block_structure_.cols.size(); ++c) {
+    const int size = block_structure_.cols[c].size;
+    const int position = block_structure_.cols[c].position;
+    ConstMatrixRef D(blocks_[c], size, size);
+    ConstVectorRef x_block(x + position, size);
+    VectorRef y_block(y + position, size);
+    y_block += D * x_block;
+  }
+}
+
+void BlockJacobiPreconditioner::LeftMultiply(const double* x, double* y) const {
+  RightMultiply(x, y);
+}
+
+}  // namespace internal
+}  // namespace ceres