1 files changed, 9 insertions, 6 deletions
diff --git a/bitsandbytes/autograd/_functions.py b/bitsandbytes/autograd/_functions.py
index 14f2660..01e7073 100644
--- a/bitsandbytes/autograd/_functions.py
+++ b/bitsandbytes/autograd/_functions.py
@@ -1,10 +1,15 @@
-from dataclasses import dataclass
-
+import operator
 import torch
-import math
 import bitsandbytes as bnb
 import bitsandbytes.functional as F
 
+from dataclasses import dataclass
+from functools import reduce  # Required in Python 3
+
+# math.prod not compatible with python < 3.8
+def prod(iterable):
+    return reduce(operator.mul, iterable, 1)
+
 tensor = torch.Tensor
 
 """
@@ -12,8 +17,6 @@ tensor = torch.Tensor
     This is particularly important for small models where outlier features 
     are less systematic and occur with low frequency.
 """
-
-
 class GlobalOutlierPooler(object):
     _instance = None
 
@@ -201,7 +204,7 @@ class MatMul8bitLt(torch.autograd.Function):
     def forward(ctx, A, B, out=None, state=MatmulLtState()):
         # default to pytorch behavior if inputs are empty
         ctx.is_empty = False
-        if math.prod(A.shape) == 0:
+        if prod(A.shape) == 0:
             ctx.is_empty = True
             ctx.A = A
             ctx.B = B