Fixing doc strings.
@@ -148,14 +148,16 @@ def fftconvolve(in1, in2, mode='full', axes=None):
in2 (cupy.ndarray): Second input. Should have the same number of
dimensions as ``in1``.
mode (str): Indicates the size of the output:
- ``'full'``: output is the full discrete linear cross-correlation
- (default)
- ``'valid'``: output consists only of those elements that do not
- rely on the zero-padding. Either ``in1`` or ``in2``
- must be at least as large as the other in every
- dimension.
- ``'same'``: output is the same size as ``in1``, centered
+
+ - ``'full'``: output is the full discrete linear \
+ cross-correlation (default)
+ - ``'valid'``: output consists only of those elements that do \
+ not rely on the zero-padding. Either ``in1`` or \
+ ``in2`` must be at least as large as the other in \
+ every dimension.
+ - ``'same'``: output is the same size as ``in1``, centered \
with respect to the 'full' output
+
axes (scalar or tuple of scalar or None): Axes over which to compute
the convolution. The default is over all axes.
@@ -218,13 +220,14 @@ def oaconvolve(in1, in2, mode="full", axes=None):
in2 (cupy.ndarray): Second input. Should have the same number of
dimensions as ``in1``.
mode (str): Indicates the size of the output:
- ``'full'``: output is the full discrete linear cross-correlation
- (default)
- ``'valid'``: output consists only of those elements that do not
- rely on the zero-padding. Either ``in1`` or ``in2``
- must be at least as large as the other in every
- dimension.
- ``'same'``: output is the same size as ``in1``, centered
+
+ - ``'full'``: output is the full discrete linear \
+ cross-correlation (default)
+ - ``'valid'``: output consists only of those elements that do \
+ not rely on the zero-padding. Either ``in1`` or \
+ ``in2`` must be at least as large as the other in \
+ every dimension.
+ - ``'same'``: output is the same size as ``in1``, centered \
with respect to the ``'full'`` output
axes (scalar or tuple of scalar or None): Axes over which to compute
the convolution. The default is over all axes.
