PyTorch张量比较不匹配问题：随机种子复现验证异常

我尝试过Stack Overflow问题《How to check if two Torch tensors or matrices are equal?》中的所有解决方案，但均未成功。我以验证随机数种子的复现性为场景，编写了如下代码：

import numpy as np
import os
import random
import torch

def seed_everything(seed):
  random.seed(seed)
  os.environ['PYTHONHASHSEED'] = str(seed)
  np.random.seed(seed)
  torch.manual_seed(seed)
  torch.cuda.manual_seed(seed)
  torch.cuda.manual_seed_all(seed) # for cases of multiple gpus
  torch.backends.cudnn.deterministic = True

seed_everything(4321)
a = torch.rand(1, 3)
print(f"Tensor a: {a}")

a_expect = torch.tensor([[0.1255, 0.5377, 0.6564]])
print(f"Tensor a_expect: {a_expect}")

equal = torch.equal(a, a_expect)
print(f"torch.equal: {equal}")

eq = torch.eq(a, a_expect)
print(f"torch.eq: {eq}")

close = torch.allclose(a, a_expect)
print(f"torch.allclose: {close}")

diff = torch.all(torch.lt(torch.abs(torch.add(a, -a_expect)), 1e-12))
print(f"torch.all(lt(abs(add,1e-12))): {diff}")

运行后输出如下：

Tensor a: tensor([[0.1255, 0.5377, 0.6564]])
Tensor a_expect: tensor([[0.1255, 0.5377, 0.6564]])
torch.equal: False
torch.eq: tensor([[False, False, False]])
torch.allclose: False
torch.all(lt(abs(add,1e-12))): False

我使用的是PyTorch 1.12.1，设备为Apple M1 Mac，降级到1.10.2后问题依旧。

更新：我发现问题在于张量打印时数值被截断，将随机张量转为列表后，显示出其真实值与预期值存在精度差异：

values = a.tolist()
print(f"Tensor values: {values}")

输出为：

Tensor values: [0.1255376935005188, 0.5376683473587036, 0.6563868522644043]

内容的提问来源于stack exchange，提问作者slashdottir