Implement pad

pytensor/tensor/pad.py

@@ -200,7 +200,7 @@
         # We could also return early in the more general case of left_length == right_length, but we don't necessarily
         # know these shapes.
         # TODO: Add rewrite to simplify in this case
         return left_stat, left_stat
 
     # Calculate statistic for the right side
     right_length = (
@@ -553,7 +553,7 @@
 
         print(pt.pad(a, (2, 3), 'linear_ramp', end_values=(5, -4)).eval())
 
-    ..testoutput::
+    .. testoutput::
 
         [ 5.  3.  1.  2.  3.  4.  5.  2. -1. -4.]
 
@@ -615,7 +615,7 @@
 
     """
     if any(value not in allowed_kwargs[mode] for value in kwargs.keys()):
         raise ValueError(
             f"Invalid keyword arguments for mode '{mode}': {kwargs.keys()}"
         )
     x = as_tensor(x, name="x")
@@ -637,7 +637,7 @@
         if mode == "median":
             # TODO: Revisit this after we implement a quantile function.
             #  See https://github.com/pymc-devs/pytensor/issues/53
             raise NotImplementedError("Median padding not implemented")
         stat_func = cast(Callable, stat_funcs[mode])
         stat_length = kwargs.get("stat_length")
         if stat_length is not None: