address comments

Author: vtavana

dpnp/dpnp_iface_manipulation.py

@@ -1848,7 +1848,7 @@ def pad(array, pad_width, mode="constant", **kwargs):
     Parameters
     ----------
     array : {dpnp.ndarray, usm_ndarray}
-        The array to pad.
+        The array of rank ``N`` to pad.
     pad_width : {sequence, array_like, int}
         Number of values padded to the edges of each axis.
         ``((before_1, after_1), ... (before_N, after_N))`` unique pad widths
@@ -1893,21 +1893,17 @@ def pad(array, pad_width, mode="constant", **kwargs):
             Padding function, see Notes.
         Default: ``"constant"``.
     stat_length : {None, int, sequence of ints}, optional
-        Used in "maximum", "mean", and "minimum". Number of
+        Used in ``"maximum"``, ``"mean"``, and ``"minimum"``. Number of
         values at edge of each axis used to calculate the statistic value.
-
         ``((before_1, after_1), ... (before_N, after_N))`` unique statistic
         lengths for each axis.
-
         ``(before, after)`` or ``((before, after),)`` yields same before
         and after statistic lengths for each axis.
-
         ``(stat_length,)`` or ``int`` is a shortcut for
         ``before = after = statistic`` length for all axes.
-
        Default: ``None``, to use the entire axis.
     constant_values : {sequence, scalar}, optional
-        Used in "constant". The values to set the padded values for each
+        Used in ``"constant"``. The values to set the padded values for each
         axis.
         ``((before_1, after_1), ... (before_N, after_N))`` unique pad constants
         for each axis.
@@ -1917,7 +1913,7 @@ def pad(array, pad_width, mode="constant", **kwargs):
         ``before = after = constant`` for all axes.
         Default: ``0``.
     end_values : {sequence, scalar}, optional
-        Used in "linear_ramp". The values used for the ending value of the
+        Used in ``"linear_ramp"``. The values used for the ending value of the
         linear_ramp and that will form the edge of the padded array.
         ``((before_1, after_1), ... (before_N, after_N))`` unique end values
         for each axis.
@@ -1927,9 +1923,9 @@ def pad(array, pad_width, mode="constant", **kwargs):
         ``before = after = constant`` for all axes.
         Default: ``0``.
     reflect_type : {"even", "odd"}, optional
-        Used in "reflect", and "symmetric". The "even" style is the
+        Used in ``"reflect"``, and ``"symmetric"``. The ``"even"`` style is the
         default with an unaltered reflection around the edge value. For
-        the "odd" style, the extended part of the array is created by
+        the ``"odd"`` style, the extended part of the array is created by
         subtracting the reflected values from two times the edge value.
         Default: ``"even"``.
 

dpnp/dpnp_utils/dpnp_utils_pad.py

@@ -216,11 +216,11 @@ def _get_stats(padded, axis, width_pair, length_pair, stat_func):
         valid area in `padded` is considered.
     stat_func : function
         Function to compute statistic. The expected signature is
-        ``stat_func(x: ndarray, axis: int, keepdims: bool) -> ndarray``.
+        ``stat_func(x: dpnp.ndarray, axis: int, keepdims: bool) -> dpnp.ndarray``.
 
     Returns
     -------
-    left_stat, right_stat : ndarray
+    left_stat, right_stat : dpnp.ndarray
         Calculated statistic for both sides of `padded`.
 
     """
@@ -642,6 +642,7 @@ def dpnp_pad(array, pad_width, mode="constant", **kwargs):
 
             # compute indices for the iteration axes, and append a trailing
             # ellipsis to prevent 0d arrays decaying to scalars
+            # TODO: replace with dpnp.ndindex when implemented
             inds = numpy.ndindex(view.shape[:-1])
             inds = (ind + (Ellipsis,) for ind in inds)
             for ind in inds:
@@ -744,7 +745,7 @@ def dpnp_pad(array, pad_width, mode="constant", **kwargs):
 
     elif mode in {"reflect", "symmetric"}:
         method = kwargs.get("reflect_type", "even")
-        include_edge = True if mode == "symmetric" else False
+        include_edge = mode == "symmetric"
         for axis, (left_index, right_index) in zip(axes, pad_width):
             if array.shape[axis] == 1 and (left_index > 0 or right_index > 0):
                 # Extending singleton dimension for 'reflect' is legacy
@@ -769,7 +770,7 @@ def dpnp_pad(array, pad_width, mode="constant", **kwargs):
                     include_edge,
                 )
 
-    elif mode == "wrap":
+    else:  # mode == "wrap":
         for axis, (left_index, right_index) in zip(axes, pad_width):
             roi = _view_roi(padded, original_area_slice, axis)
             original_period = padded.shape[axis] - right_index - left_index