def _get_dataset(self, X, y=None):
        """
        Construct a pylearn2 dataset.

        Parameters
        ----------
        X : array_like
            Training examples.
        y : array_like, optional
            Labels.
        """
        from pylearn2.datasets import DenseDesignMatrix

        X = np.asarray(X)
        assert X.ndim > 1
        if y is not None:
            y = self._get_labels(y)
        if X.ndim == 2:
            return DenseDesignMatrix(X=X, y=y)
        return DenseDesignMatrix(topo_view=X, y=y)
def _get_dataset(self, X, y=None):
        
        from pylearn2.datasets import DenseDesignMatrix

        X = np.asarray(X)
        assert X.ndim > 1
        if y is not None:
            y = self._get_labels(y)
        if X.ndim == 2:
            return DenseDesignMatrix(X=X, y=y)
        return DenseDesignMatrix(topo_view=X, y=y)
def _get_dataset ( self , X , y = None ) : from pylearn2 . datasets import DenseDesignMatrix X = np . asarray ( X ) assert X . ndim > 1 if y is not None : y = self . _get_labels ( y ) if X . ndim == 2 : return DenseDesignMatrix ( X = X , y = y ) return DenseDesignMatrix ( topo_view = X , y = y )
Construct a pylearn2 dataset.

        Parameters
        ----------
        X : array_like
            Training examples.
        y : array_like, optional
            Labels.
Construct a pylearn2 dataset .