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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2019 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// 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)
+
+#ifndef CERES_PUBLIC_TINY_SOLVER_COST_FUNCTION_ADAPTER_H_
+#define CERES_PUBLIC_TINY_SOLVER_COST_FUNCTION_ADAPTER_H_
+
+#include "Eigen/Core"
+#include "ceres/cost_function.h"
+#include "glog/logging.h"
+
+namespace ceres {
+
+// An adapter class that lets users of TinySolver use
+// ceres::CostFunction objects that have exactly one parameter block.
+//
+// The adapter allows for the number of residuals and the size of the
+// parameter block to be specified at compile or run-time.
+//
+// WARNING: This object is not thread-safe.
+//
+// Example usage:
+//
+//  CostFunction* cost_function = ...
+//
+// Number of residuals and parameter block size known at compile time:
+//
+//   TinySolverCostFunctionAdapter<kNumResiduals, kNumParameters>
+//   cost_function_adapter(*cost_function);
+//
+// Number of residuals known at compile time and the parameter block
+// size not known at compile time.
+//
+//   TinySolverCostFunctionAdapter<kNumResiduals, Eigen::Dynamic>
+//   cost_function_adapter(*cost_function);
+//
+// Number of residuals not known at compile time and the parameter
+// block size known at compile time.
+//
+//   TinySolverCostFunctionAdapter<Eigen::Dynamic, kParameterBlockSize>
+//   cost_function_adapter(*cost_function);
+//
+// Number of residuals not known at compile time and the parameter
+// block size not known at compile time.
+//
+//   TinySolverCostFunctionAdapter cost_function_adapter(*cost_function);
+//
+template <int kNumResiduals = Eigen::Dynamic,
+          int kNumParameters = Eigen::Dynamic>
+class TinySolverCostFunctionAdapter {
+ public:
+  typedef double Scalar;
+  enum ComponentSizeType {
+    NUM_PARAMETERS = kNumParameters,
+    NUM_RESIDUALS = kNumResiduals
+  };
+
+  // This struct needs to have an Eigen aligned operator new as it contains
+  // fixed-size Eigen types.
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
+
+  TinySolverCostFunctionAdapter(const CostFunction& cost_function)
+      : cost_function_(cost_function) {
+    CHECK_EQ(cost_function_.parameter_block_sizes().size(), 1)
+        << "Only CostFunctions with exactly one parameter blocks are allowed.";
+
+    const int parameter_block_size = cost_function_.parameter_block_sizes()[0];
+    if (NUM_PARAMETERS == Eigen::Dynamic || NUM_RESIDUALS == Eigen::Dynamic) {
+      if (NUM_RESIDUALS != Eigen::Dynamic) {
+        CHECK_EQ(cost_function_.num_residuals(), NUM_RESIDUALS);
+      }
+      if (NUM_PARAMETERS != Eigen::Dynamic) {
+        CHECK_EQ(parameter_block_size, NUM_PARAMETERS);
+      }
+
+      row_major_jacobian_.resize(cost_function_.num_residuals(),
+                                 parameter_block_size);
+    }
+  }
+
+  bool operator()(const double* parameters,
+                  double* residuals,
+                  double* jacobian) const {
+    if (!jacobian) {
+      return cost_function_.Evaluate(&parameters, residuals, NULL);
+    }
+
+    double* jacobians[1] = {row_major_jacobian_.data()};
+    if (!cost_function_.Evaluate(&parameters, residuals, jacobians)) {
+      return false;
+    }
+
+    // The Function object used by TinySolver takes its Jacobian in a
+    // column-major layout, and the CostFunction objects use row-major
+    // Jacobian matrices. So the following bit of code does the
+    // conversion from row-major Jacobians to column-major Jacobians.
+    Eigen::Map<Eigen::Matrix<double, NUM_RESIDUALS, NUM_PARAMETERS>>
+        col_major_jacobian(jacobian, NumResiduals(), NumParameters());
+    col_major_jacobian = row_major_jacobian_;
+    return true;
+  }
+
+  int NumResiduals() const { return cost_function_.num_residuals(); }
+  int NumParameters() const {
+    return cost_function_.parameter_block_sizes()[0];
+  }
+
+ private:
+  const CostFunction& cost_function_;
+  mutable Eigen::Matrix<double, NUM_RESIDUALS, NUM_PARAMETERS, Eigen::RowMajor>
+      row_major_jacobian_;
+};
+
+}  // namespace ceres
+
+#endif  // CERES_PUBLIC_TINY_SOLVER_COST_FUNCTION_ADAPTER_H_