change at.diff to slicing + subtraction

aesara/tensor/extra_ops.py

@@ -3,6 +3,7 @@ from typing import Iterable, Tuple, Union
 
 import numpy as np
 import numpy.core.numeric
+from numpy.core.multiarray import normalize_axis_index
 
 import aesara
 from aesara.gradient import (
@@ -483,7 +484,7 @@ class DiffOp(Op):
 
     def make_node(self, x):
         x = at.as_tensor_variable(x)
-        axis = numpy.core.numeric.normalize_axis_index(self.axis, x.ndim)
+        axis = normalize_axis_index(self.axis, x.ndim)
         shape = [None] * x.type.ndim
         for i, shape_i in enumerate(x.type.shape):
             if shape_i is None:
@@ -533,7 +534,7 @@ def diff(x, n=1, axis=-1):
 
     The first order difference is given by ``out[i] = a[i + 1] - a[i]``
     along the given `axis`, higher order differences are calculated by
-    using `diff` recursively. This wraps ``numpy.diff``.
+    using `diff` recursively. This is heavily inspired by ``numpy.diff``.
 
     Parameters
     ----------
@@ -548,7 +549,20 @@ def diff(x, n=1, axis=-1):
     .. versionadded:: 0.6
 
     """
-    return DiffOp(n=n, axis=axis)(x)
+    ndim = x.ndim
+    axis = normalize_axis_index(axis, ndim)
+        
+    slice1 = [slice(None)] * ndim
+    slice2 = [slice(None)] * ndim
+    slice1[axis] = slice(1, None)
+    slice2[axis] = slice(None, -1)
+    slice1 = tuple(slice1)
+    slice2 = tuple(slice2)
+    
+    for _ in range(n):
+        x = x[slice1] - x[slice2]
+    
+    return x
 
 
 def bincount(x, weights=None, minlength=None, assert_nonneg=False):