Support for using the GPU by default, then falling back to the CPU if…

… none is found.

README.rst

@@ -12,7 +12,6 @@ Upcoming Features
 
 * An example that covers hand-written digit recognition from the MNIST dataset.
 * Better error checking for the layer specifications, useful messages otherwise.
-* Support for automatically using the GPU, with manually specified CPU fallback.
 * Use pylearn2's monitoring code to stop training upon detecting convergence.
 
 

sknn/mlp.py

@@ -2,13 +2,16 @@
 
 __all__ = ['MultiLayerPerceptronRegressor', 'MultiLayerPerceptronClassifier']
 
-
+import os
 import logging
 log = logging.getLogger('sknn')
 
+# By default, we force Theano to use a GPU and fallback to CPU, using 32-bits.
+# This must be done in the code before Theano is imported for the first time.
+os.environ['THEANO_FLAGS'] = "device=gpu,floatX=float32"
+import theano
 
 import numpy
-import theano
 import sklearn.base
 import sklearn.preprocessing
 
@@ -322,6 +325,9 @@ def predict(self, X):
             y = numpy.zeros((X.shape[0], self.unit_counts[-1]))
             self.initialize(X, y)
 
+        if X.dtype != numpy.float32:
+            X = X.astype(numpy.float32)
+
         if self.is_convolution:
             X = numpy.array([X]).transpose(1,2,3,0)