In the torch tensor case below, why do s * pi and t * pi have different precision ?

```
#! /usr/bin/env python3
r'''
Expected Results:
s * pi - t * pi as numpy arrays = [0.]
s * pi - t * pi as torch tesors = tensor([0.], dtype=torch.float64)
Actual Results:
s * pi - t * pi as numpy arrays = [0.]
s * pi - t * pi as torch tesors = tensor([-8.7423e-08], dtype=torch.float64)
'''
import torch
import numpy
#
# pi
pi = numpy.pi
#
# s, t
s = numpy.ones(1)
t = numpy.array( [1.0] )
print( 's * pi - t * pi as numpy arrays = ', s * pi - t * pi )
#
# s, t
s = torch.tensor( numpy.ones(1) )
t = torch.tensor( [1.0] )
print( 's * pi - t * pi as torch tesors = ', s * pi - t * pi )
```