Describe the issue:
I found that dask.cumprod will bring different results with numpy.cumprod as follow.
I think this may be a bug in dask.

Minimal Complete Verifiable Example:

import numpy as np
import dask.array as da

print(np.cumprod(np.array([1.5,2.5]),dtype=int))
print(da.cumprod(da.array([1.5, 2.5]), dtype=int).compute())

Output:

[1 2]
[1.5  3.75]

Anything else we need to know?:

Environment:

• Dask version: 2025.4.1
• Python version: 3.10.0
• Operating System: Linux 6.11.0-25-generic Ubuntu 24.04.1 x86_64 GNU/Linux
• Install method (conda, pip, source): pip
• Numpy version: 2.2.4