small code clean up (and remove potential bug that currently don't happen)

theano/sandbox/cuda/opt.py

@@ -43,6 +43,7 @@ from theano.sandbox.cuda.var import CudaNdarrayConstant
 from theano.scan_module import scan_utils, scan_op, scan_opt
 from theano.tensor.blas import _is_real_vector, _is_real_matrix
 from theano.tensor import nlinalg
+from theano.tensor.nnet.Conv3D import Conv3D
 
 #optdb.print_summary()  # shows what is currently registered
 
@@ -1236,17 +1237,18 @@ def local_conv_fft_full(node):
 gpu_optimizer.register("conv_fft_valid", local_conv_fft_valid)
 gpu_optimizer.register("conv_fft_full", local_conv_fft_full)
 
-from theano.tensor.nnet.Conv3D import Conv3D
+
 @local_optimizer([Conv3D])
 def local_conv3d_fft(node):
+    if not isinstance(node.op, Conv3D):
+        return
     try:
         stride_x = tensor.get_scalar_constant_value(node.inputs[3][0])
         stride_y = tensor.get_scalar_constant_value(node.inputs[3][1])
         stride_z = tensor.get_scalar_constant_value(node.inputs[3][2])
     except tensor.NotScalarConstantError:
         return False
-    if (isinstance(node.op, Conv3D) and
-        (stride_x, stride_y, stride_z) == (1, 1, 1)):
+    if (stride_x, stride_y, stride_z) == (1, 1, 1):
         # we import conv3d_fft locally to avoid pycuda warnings
         from theano.sandbox.cuda.fftconv import conv3d_fft
         # Shuffle inputs signal from (b, 0, 1, t, c) to (b, c, 0, 1, t)
@@ -1256,7 +1258,7 @@ def local_conv3d_fft(node):
         f = node.inputs[1]
         f = gpu_from_host(f.dimshuffle(0, 4, 1, 2, 3))
         # filter flip
-        f = f[:,:,::-1,::-1,::-1]
+        f = f[:, :, ::-1, ::-1, ::-1]
         rval = conv3d_fft(x, f, border_mode='valid', pad_last_dim=True)
         # Shuffle from (oc, c, 0, 1, t) to (oc, 0, 1, t, c)
         return [rval.dimshuffle(0, 2, 3, 4, 1) + node.inputs[2]]