Documentation changes. Combpressing tuple of two identical integers

theano/gpuarray/blas.py

@@ -927,8 +927,11 @@ class GpuCorrMM(BaseGpuCorrMM):
         ``'valid'`` for ``(0, 0)`` (valid convolution, no padding), ``'full'``
         for ``(kernel_rows - 1, kernel_columns - 1)`` (full convolution),
         ``'half'`` for ``(kernel_rows // 2, kernel_columns // 2)`` (same
-        convolution for odd-sized kernels). Note that the two widths are each
-        applied twice, once per side (left and right, top and bottom).
+        convolution for odd-sized kernels).
+        If it is a tuple containing 2 pairs of integers, then these specify
+        the padding to be applied on each side ((left, right), (top, bottom)).
+        Otherwise, each width is applied twice, once per side (left and right,
+        top and bottom).
     subsample
         The subsample operation applied to each output image.
         Should be a tuple with 2 elements.

theano/tensor/nnet/abstract_conv.py

@@ -1971,16 +1971,22 @@ class BaseAbstractConv(Op):
                 raise ValueError(
                     'invalid border_mode {}, which must be a '
                     'tuple of length {}'.format(border_mode, convdim))
+            new_border_mode = ()
             for mode in border_mode:
-                if isinstance(mode, tuple) and convdim != 2:
-                    raise NotImplementedError(
-                        'Asymmetric padding not implemented for {}D'.format(convdim))
                 if not((isinstance(mode, integer_types) and mode >= 0) or
                         (isinstance(mode, tuple) and len(mode) == 2 and min(mode) >= 0 and
                          all(isinstance(m, integer_types) for m in mode))):
                     raise ValueError(
                         'invalid border mode {}. The tuple can only contain integers '
                         ' or pairs of integers'.format(border_mode))
+                if isinstance(mode, tuple):
+                    if convdim != 2:
+                        raise NotImplementedError(
+                            'Asymmetric padding not implemented for {}D'.format(convdim))
+                    if mode[0] == mode[1]:
+                        mode = mode[0]
+                new_border_mode += (mode,)
+            border_mode = new_border_mode
         elif border_mode not in ('valid', 'full', 'half'):
             raise ValueError(
                 'invalid border_mode {}, which must be either '

theano/tensor/nnet/corr.py

@@ -603,8 +603,11 @@ class CorrMM(BaseCorrMM):
         ``'valid'`` for ``(0, 0)`` (valid convolution, no padding), ``'full'``
         for ``(kernel_rows - 1, kernel_columns - 1)`` (full convolution),
         ``'half'`` for ``(kernel_rows // 2, kernel_columns // 2)`` (same
-        convolution for odd-sized kernels). Note that the two widths are each
-        applied twice, once per side (left and right, top and bottom).
+        convolution for odd-sized kernels).
+        If it is a tuple containing 2 pairs of integers, then these specify
+        the padding to be applied on each side ((left, right), (top, bottom)).
+        Otherwise, each width is applied twice, once per side (left and right,
+        top and bottom).
     subsample
         The subsample operation applied to each output image.
         Should be a tuple with 2 elements.