Merge pull request #2297 from f0k/metaopt-again

doc/library/tensor/nnet/conv.txt

@@ -46,6 +46,16 @@
     into Theano, and an implementation by Alex Krizhevsky available via
     Pylearn2. See the documentation below on how to use them.
 
+    As of November 24th, 2014, you can also use a meta-optimizer to
+    automatically choose the fastest implementation for each specific
+    convolution in your graph. For each instance, it will compile and benchmark
+    each applicable implementation of the ones listed below and choose the
+    fastest one. As performance is dependent on input and filter shapes, this
+    only works for operations introduced via nnet.conv2d with fully specified
+    shape information.
+    Enable it via the Theano flag ``optimizer_including=conv_meta``, and
+    optionally set it to verbose mode via the flag `metaopt.verbose=1`.
+
 
 TODO: Give examples on how to use these things! They are pretty complicated.
 

theano/gof/opt.py

@@ -823,6 +823,10 @@ class LocalOptimizer(object):
                 (' ' * level), self.__class__.__name__, id(self))
 
 
+theano.configparser.AddConfigVar('metaopt.verbose',
+        "Enable verbose output for meta optimizers",
+        theano.configparser.BoolParam(False), in_c_key=False)
+
 class LocalMetaOptimizer(LocalOptimizer):
     """Base class for meta-optimizers that try a set of LocalOptimizers
     to replace a node and choose the one that executes the fastest"""
@@ -830,7 +834,7 @@ class LocalMetaOptimizer(LocalOptimizer):
     def __init__(self, tracks=None, optimizers=()):
         self._tracks = tracks
         self.optimizers = list(optimizers)
-        self.verbose = False
+        self.verbose = config.metaopt.verbose
 
     def register(self, optimizer):
         self.optimizers.append(optimizer)
@@ -876,10 +880,7 @@ class LocalMetaOptimizer(LocalOptimizer):
             outputs = opt.transform(node)
             if outputs:
                 try:
-                    fn = theano.function([],
-                                         [theano.Out(output, borrow=True)
-                                          for output in outputs],
-                                         givens=givens)
+                    fn = theano.function([], outputs, givens=givens)
                     timing = min(self.time_call(fn) for _ in range(3))
                 except Exception as e:
                     if self.verbose:

theano/sandbox/cuda/opt.py

@@ -1361,14 +1361,9 @@ class LocalCudaMetaOptimizer(LocalMetaOptimizer):
 
 # Convolution Meta-optimizer
 
-theano.configparser.AddConfigVar('conv_meta.verbose',
-        "Enable verbose output for conv_meta optimizer",
-        theano.configparser.BoolParam(False), in_c_key=False)
-
 class ConvMetaOptimizer(LocalCudaMetaOptimizer):
     def __init__(self, optimizers):
         super(ConvMetaOptimizer, self).__init__([GpuConv], optimizers)
-        self.verbose = config.conv_meta.verbose
 
     def provide_inputs(self, node, inputs):
         # We need to provide dummy data for the given inputs.