Fixed wrong input for training in Guide; added check to detect that in future.

bob/learn/mlp/cxx/backprop.cpp

@@ -172,6 +172,8 @@ void bob::learn::mlp::BackProp::train(bob::learn::mlp::Machine& machine,
   }
   bob::core::array::assertSameDimensionLength(getBatchSize(), input.extent(0));
   bob::core::array::assertSameDimensionLength(getBatchSize(), target.extent(0));
+  bob::core::array::assertSameDimensionLength(machine.inputSize(), input.extent(1));
+  bob::core::array::assertSameDimensionLength(machine.outputSize(), target.extent(1));
   train_(machine, input, target);
 }
 

bob/learn/mlp/cxx/rprop.cpp

@@ -216,6 +216,8 @@ void bob::learn::mlp::RProp::train(bob::learn::mlp::Machine& machine,
   }
   bob::core::array::assertSameDimensionLength(getBatchSize(), input.extent(0));
   bob::core::array::assertSameDimensionLength(getBatchSize(), target.extent(0));
+  bob::core::array::assertSameDimensionLength(machine.inputSize(), input.extent(1));
+  bob::core::array::assertSameDimensionLength(machine.outputSize(), target.extent(1));
   train_(machine, input, target);
 }
 

doc/guide.rst

@@ -116,7 +116,7 @@ available MLP trainers in two different 2D `NumPy`_ arrays, one for the input
 .. doctest::
    :options: +NORMALIZE_WHITESPACE
 
-   >>> d0 = numpy.array([[.3, .7]]) # input
+   >>> d0 = numpy.array([[.3, .7, .5]]) # input
    >>> t0 = numpy.array([[.0]]) # target
 
 The class used to train a MLP [1]_ with backpropagation [2]_ is