C++ API¶

The C++ API of bob.learn.mlp allows users to leverage from automatic converters for classes in bob.learn.mlp. To use the C API, clients should first, include the header file <bob.learn.mlp.h> on their compilation units and then, make sure to call once import_bob_learn_mlp() at their module instantiation, as explained at the Python manual.

Here is a dummy C example showing how to include the header and where to call the import function:

#include <bob.learn.mlp/api.h>

PyMODINIT_FUNC initclient(void) {

  PyObject* m Py_InitModule("client", ClientMethods);

  if (!m) return 0;

  if (import_bob_blitz() < 0) return 0;
  if (import_bob_io() < 0) return 0;
  if (import_bob_learn_activation() < 0) return 0;
  if (import_bob_learn_mlp() < 0) return 0;

  return m;

}

Machine¶

type PyBobLearnMLPMachineObject¶

The pythonic object representation for a bob.learn.mlp.Machine object.

typedef struct {
  PyObject_HEAD
  bob::learn::mlp::Machine* cxx;
} PyBobLearnMLPMachineObject;

bob::learn::mlp::Machine *cxx¶: A pointer to the machine implentation in C++.

int PyBobLearnMLPMachine_Check(PyObject *o)¶: Checks if the input object o is a PyBobLearnMLPMachineObject. Returns 1 if it is, and 0 otherwise.

Cost¶

type PyBobLearnCostObject¶

The pythonic object representation for a bob.learn.mlp.Cost object. It is the base class of all derive cost types available in Bob.

typedef struct {
  PyObject_HEAD
  boost::shared_ptr<bob::learn::mlp::Cost> cxx;
} PyBobLearnCostObject;

boost::shared_ptr<bob::learn::mlp::Cost> cxx¶

A pointer to the cost object implemented in C++. The cost object is an abstract interface. You cannot instantiate a cost from scratch, but only through its inherited classes.

We use a boost shared pointer to hold this pointer since it makes interaction with the C++ library and the management of responsibilities a bit easier.

int PyBobLearnCost_Check(PyObject *o)¶: Checks if the input object o is a PyBobLearnCostObject. Returns 1 if it is, and 0 otherwise.

Note

These are the cost object specializations you can use from Python:

For each of those types, object types in C exist.

PyObject *PyBobLearnCost_NewFromCost(boost::shared_ptr<bob::learn::mlp::Cost>)¶

Builds a new cost object from a shared pointer to the C++ equivalent.

Returns the object on success or a NULL pointer on failure.

Data Shuffler¶

type PyBobLearnDataShufflerObject¶

The pythonic representation for a bob.learn.mlp.DataShuffler object.

typedef struct {
  PyObject_HEAD
  bob::learn::mlp::DataShuffler* cxx;
} PyBobLearnCostObject;

bob::learn::mlp::DataShuffler *cxx¶: A pointer to the data shuffler object implemented in C++.

int PyBobLearnDataShuffler_Check(PyObject *o)¶: Checks if the input object o is a PyBobLearnDataShufflerObject. Returns 1 if it is, and 0 otherwise.

Trainers¶

type PyBobLearnMLPTrainerObject¶

The pythonic representation for a bob.learn.mlp.Trainer object. All back-propagation-based trainers should inherit from this type as it implements most of the basic functionality needed by such a learning technique.

typedef struct {
  PyObject_HEAD
  bob::learn::mlp::Trainer* cxx;
} PyBobLearnCostObject;

bob::learn::mlp::Trainer *cxx¶: A pointer to the base trainer object implemented in C++.

int PyBobLearnMLPTrainer_Check(PyObject *o)¶: Checks if the input object o is a PyBobLearnMLPTrainerObject. Returns 1 if it is, and 0 otherwise.

type PyBobLearnBackPropObject¶

The pythonic representation for a bob.learn.mlp.BackProp object. All back-propagation-based trainers should inherit from this type as it implements most of the basic functionality needed by such a learning technique.

typedef struct {
  PyBobLearnMLPTrainerObject parent;
  bob::learn::mlp::BackProp* cxx;
} PyBobLearnCostObject;

PyBobLearnMLPTrainerObject parent¶: The parent abstract class pointer. Use parent.cxx to access the abstract C++ base interface.

bob::learn::mlp::BackProp *cxx¶: A pointer to the derived trainer object implemented in C++.

int PyBobLearnBackProp_Check(PyObject *o)¶: Checks if the input object o is a PyBobLearnBackPropObject. Returns 1 if it is, and 0 otherwise.

type PyBobLearnRPropObject¶

The pythonic representation for a bob.learn.mlp.RProp object. All back-propagation-based trainers should inherit from this type as it implements most of the basic functionality needed by such a learning technique.

typedef struct {
  PyBobLearnMLPTrainerObject parent;
  bob::learn::mlp::RProp* cxx;
} PyBobLearnCostObject;

PyBobLearnMLPTrainerObject parent¶: The parent abstract class pointer. Use parent.cxx to access the abstract C++ base interface.

bob::learn::mlp::RProp *cxx¶: A pointer to the derived trainer object implemented in C++.

int PyBobLearnRProp_Check(PyObject *o)¶: Checks if the input object o is a PyBobLearnRPropObject. Returns 1 if it is, and 0 otherwise.

Pure C/C++ API¶

As explained above, each PyObject produced by this library contains a pointer to a pure C++ implementation of a similar object. The C++ of such objects is described in this section.