Renamed a variable because I gave it a ridiculously long name.

theano/sandbox/cuda/fftconv.py

@@ -370,7 +370,7 @@ def mult_and_reduce(input_fft_v, filters_fft_v, input_shape=None,
 
 
 def conv2d_fft(input, filters, image_shape=None, filter_shape=None,
-               border_mode='valid', want_padding_on_last_input_dimension=False):
+               border_mode='valid', pad_last_dim=False):
     """
     expects bc01 input
     performs a valid/full convolution
@@ -380,10 +380,10 @@ def conv2d_fft(input, filters, image_shape=None, filter_shape=None,
 
     border_mode: 'valid' of 'full'
 
-    want_padding_on_last_input_dimension: This code does not support
+    pad_last_dim: This code does not support
     images for which the last dimension (the "width") is odd. To support
     this, you can either pad your images on your own, or call this function
-    with the `want_padding_on_last_input_dimension` flag set to `True`.
+    with the `pad_last_dim` flag set to `True`.
     This introduces an extra copying step and consumes memory.
     The return value will still be of the appropriate shape because
     the padding is trimmed right before the output is returned.
@@ -404,7 +404,7 @@ def conv2d_fft(input, filters, image_shape=None, filter_shape=None,
     # pad filters/image to output shape
     if border_mode == 'valid':
         o0 = i0
-        if want_padding_on_last_input_dimension:
+        if pad_last_dim:
             o1 = i1 + 1
             input_padded = T.zeros((b, ic, o0, o1), dtype='float32')
             input_padded = T.set_subtensor(input_padded[:, :, :i0, :i1],
@@ -459,7 +459,7 @@ def conv2d_fft(input, filters, image_shape=None, filter_shape=None,
 
     # slice because the convolution was circular, we need it to be valid
     if border_mode == 'valid':
-        if want_padding_on_last_input_dimension:
+        if pad_last_dim:
             output = output_circ[:, :, f0 - 1:, f1 - 1:(o1-1)]
         else:
             output = output_circ[:, :, f0 - 1:, f1 - 1:o1]