From 62441815bc733c9e75d32dd65305a16aaebd317a Mon Sep 17 00:00:00 2001 From: Tim Dettmers Date: Mon, 8 Aug 2022 05:20:36 -0700 Subject: Removed prod for Python <= 3.7 compatibility. --- bitsandbytes/autograd/_functions.py | 14 ++++++++------ setup.py | 2 +- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/bitsandbytes/autograd/_functions.py b/bitsandbytes/autograd/_functions.py index 14f2660..a5446b7 100644 --- a/bitsandbytes/autograd/_functions.py +++ b/bitsandbytes/autograd/_functions.py @@ -1,10 +1,14 @@ -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 + +def prod(iterable): + return reduce(operator.mul, iterable, 1) + tensor = torch.Tensor """ @@ -12,8 +16,6 @@ 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 +203,7 @@ 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 diff --git a/setup.py b/setup.py index 67b655d..c425ca7 100644 --- a/setup.py +++ b/setup.py @@ -18,7 +18,7 @@ def read(fname): setup( name=f"bitsandbytes", - version=f"0.31.4", + version=f"0.31.5", author="Tim Dettmers", author_email="dettmers@cs.washington.edu", description="8-bit optimizers and matrix multiplication routines.", -- cgit v1.2.3