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Split out starting the AD process vs. propagating it, is more efficient than starting with a useless identity matrix

release/4.3a0
dellaert 2014-10-05 19:27:52 +02:00
parent ff9dd8eb8d
commit 5b13306104
2 changed files with 23 additions and 15 deletions
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35
gtsam_unstable/nonlinear/Expression-inl.h
View File

@ -135,6 +135,7 @@ struct JacobianTrace {
T value() const {
return t;
}
virtual void reverseAD(JacobianMap& jacobians) const = 0;
virtual void reverseAD(const Matrix& H, JacobianMap& jacobians) const = 0;
};
@ -212,9 +213,11 @@ public:
/// Trace structure for reverse AD
struct Trace: public JacobianTrace<T> {
/// Return value and derivatives
/// If the expression is just a constant, we do nothing
virtual void reverseAD(JacobianMap& jacobians) const {
}
/// Base case: we simply ignore the given df/dT
virtual void reverseAD(const Matrix& H, JacobianMap& jacobians) const {
// Base case: don't touch jacobians
}
};
@ -269,9 +272,13 @@ public:
/// Trace structure for reverse AD
struct Trace: public JacobianTrace<T> {
Key key;
/// Return value and derivatives
/// If the expression is just a leaf, we just insert an identity matrix
virtual void reverseAD(JacobianMap& jacobians) const {
size_t n = T::Dim();
jacobians.add(key, Eigen::MatrixXd::Identity(n, n));
}
/// Base case: given df/dT, add it jacobians with correct key and we are done
virtual void reverseAD(const Matrix& H, JacobianMap& jacobians) const {
// Base case: just insert a new H in the JacobianMap with correct key
jacobians.add(key, H);
}
};
@ -338,11 +345,12 @@ public:
struct Trace: public JacobianTrace<T> {
boost::shared_ptr<JacobianTrace<A> > trace1;
Matrix H1;
/// Return value and derivatives
/// Start the reverse AD process
virtual void reverseAD(JacobianMap& jacobians) const {
trace1->reverseAD(H1, jacobians);
}
/// Given df/dT, multiply in dT/dA and continue reverse AD process
virtual void reverseAD(const Matrix& H, JacobianMap& jacobians) const {
// This is a top-down calculation
// The end-result needs Jacobians to all leaf nodes.
// Since this is not a leaf node, we compute what is needed for leaf nodes here
trace1->reverseAD(H * H1, jacobians);
}
};
@ -421,12 +429,13 @@ public:
boost::shared_ptr<JacobianTrace<A1> > trace1;
boost::shared_ptr<JacobianTrace<A2> > trace2;
Matrix H1, H2;
/// Return value and derivatives
/// Start the reverse AD process
virtual void reverseAD(JacobianMap& jacobians) const {
trace1->reverseAD(H1, jacobians);
trace2->reverseAD(H2, jacobians);
}
/// Given df/dT, multiply in dT/dA and continue reverse AD process
virtual void reverseAD(const Matrix& H, JacobianMap& jacobians) const {
// This is a top-down calculation
// The end-result needs Jacobians to all leaf nodes.
// Since this is not a leaf node, we compute what is needed for leaf nodes here
// The binary node represents a fork in the tree, and hence we will get two Augmented maps
trace1->reverseAD(H * H1, jacobians);
trace2->reverseAD(H * H2, jacobians);
}

3
gtsam_unstable/nonlinear/Expression.h
View File

@ -107,8 +107,7 @@ public:
#ifdef REVERSE_AD
boost::shared_ptr<JacobianTrace<T> > trace = root_->traceExecution(values);
Augmented<T> augmented(trace->value());
size_t n = T::Dim();
trace->reverseAD(Eigen::MatrixXd::Identity(n, n), augmented.jacobians());
trace->reverseAD(augmented.jacobians());
return augmented;
#else
return root_->forward(values);