It’s not a rounding error, it’s about print. PyTorch uses less precision to print.
a-b.numpy()
Out[3]: array([0., 0., 0.])
np.linalg.norm((a-b.numpy()))
Out[4]: 0.0

print(b[0])
tensor(0.1078, dtype=torch.float64)
print(b[0].item())
0.107790701