Port some for GpuConv change to the new back-end. (fix test error in new back-end.

theano/sandbox/gpuarray/conv.py

@@ -27,15 +27,23 @@ class GpuConv(gof.Op):
             logical_kern_hw=None,
             logical_kern_align_top=True,
             version=-1,
+            direction_hint=None,
             verbose=0,
             kshp=None,
             imshp=None,
-            max_threads_dim0=None):
+            max_threads_dim0=None,
+            nkern=None,
+            bsize=None,
+            fft_opt=True):
         """
         :param version: each version of c_code implements many kernels for the
                         convolution. By default we try to guess the best one.
                         You can force one version with this parameter. This
                         parameter is used by the tests.
+        :param direction_hint: 'forward', 'bprop weights' or 'bprop inputs'.
+                        Serves as a hint for graph optimizers replacing
+                        GpuConv by other implementations. If the GpuConv is
+                        inserted automatically, we take its value from ConvOp.
         :param verbose: for value of 1,2 and 3. Print more information during
                         the execution of the convolution. Mostly used for
                         optimization or debugging.
@@ -49,6 +57,19 @@ class GpuConv(gof.Op):
         :param max_threads_dim0: The maximum number of threads for the
                         block size dimensions 0 (blockDim.x) used by the
                         GPU function.
+        :param nkern:   The number of kernels. Not used for this op, but can be
+                        used by graph optimizers to select a more optimal
+                        convolution implementation. If the GpuConv op is inserted
+                        automatically, we take its value from the Conv op.
+        :param bsize:   The batch size. Not used for this op, but can be
+                        used by graph optimizers to select a more optimal
+                        convolution implementation. If the GpuConv op is inserted
+                        automatically, we take its value from the Conv op.
+        :param fft_opt: deactivate fft_opt optimization at the op level when
+                        set to False. Note that by default fft optimization
+                        aren't enabled. See
+                        :ref:`convolution documentation <libdoc_tensor_nnet_conv>`
+                        to enable them.
 
         """
         self.border_mode = border_mode
@@ -69,10 +90,14 @@ class GpuConv(gof.Op):
         self.logical_kern_hw = logical_kern_hw
         self.logical_kern_align_top = logical_kern_align_top
         self.version = version
+        self.direction_hint = direction_hint
         self.verbose = verbose
         self.kshp = kshp
         self.imshp = imshp
         self.max_threads_dim0 = max_threads_dim0
+        self.nkern = nkern
+        self.bsize = bsize
+        self.fft_opt = fft_opt
 
     def __eq__(self, other):
         return type(self) == type(other) \
@@ -93,6 +118,8 @@ class GpuConv(gof.Op):
             self.imshp = None
         if not hasattr(self, "max_threads_dim0"):
             self.max_threads_dim0 = None
+        if not hasattr(self, "direction_hint"):
+            self.direction_hint = None
 
     def __hash__(self):
         # don't use hash(self.version) as hash(-1)==-2 and

theano/sandbox/gpuarray/opt.py

@@ -669,8 +669,12 @@ def local_gpu_conv(node):
                       logical_kern_align_top=op.kshp_logical_top_aligned,
                       kshp=op.kshp,
                       version=op.version,
+                      direction_hint=op.direction_hint,
                       verbose=op.verbose,
                       imshp=op.imshp,
+                      nkern=op.nkern,
+                      bsize=op.bsize,
+                      fft_opt=op.fft_opt
                       )
         if op.imshp_logical is not None:
             logical_img_hw = op.imshp_logical[1:3]