Pytorch--Tensor， Numpy--Array，Python--List 相互之间的转换。

梦里梦外; 2021-10-15 08:25 383阅读 0赞

# 1.1 List --> Arrary: np.array(List 变量) #

a = [1, 2, 3, 4]
    b = np.array(a)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zNzU4OTU3NQ_size_16_color_FFFFFF_t_70]

# 1.2 Arrary --> List: Array 变量.tolist() #

a = [1, 2, 3, 4]
    b = np.array(a)
    c = b.tolist()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zNzU4OTU3NQ_size_16_color_FFFFFF_t_70 1]

# 2.1 List --> Tensor: torch.Tensor(List 变量) #

a = [1, 2, 3, 4]
    b = torch.Tensor(a)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zNzU4OTU3NQ_size_16_color_FFFFFF_t_70 2]

# 2.2 Tensor --> List: Tensor 变量.numpy().tolist() #

a = [1, 2, 3, 4]
    b = torch.Tensor(a)
    c = b.numpy().tolist()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zNzU4OTU3NQ_size_16_color_FFFFFF_t_70 3]  
这里 c 和 a 的差异在于 List 转为 Tensor 的时候默认 Tensor 中的数据为 float 类型，所以转回来的时候会变为浮点数。

# 3.1 Array --> Tensor: torch.from\_numpy(Array 变量) #

a = [1, 2, 3, 4]
    b = np.array(a)
    c = torch.from_numpy(b)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zNzU4OTU3NQ_size_16_color_FFFFFF_t_70 4]

# 3.2 Tensor --> Array: torch.numpy(Tensor 变量) #

a = [1, 2, 3, 4]
    b = np.array(a)
    c = torch.from_numpy(b)
    d = c.numpy()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zNzU4OTU3NQ_size_16_color_FFFFFF_t_70 5]

如果需要转换 GPU 上的张量 Tensor，需要将其转换到 CPU 上，例如 GPU 上的 Tensor ：

a = [1, 2, 3, 4]
    b = np.array(a)
    c = torch.from_numpy(b).cuda()
    d = c.numpy()

会报错： TypeError: can’t convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.  
这时应该使用

d = c.cpu().numpy()

先放回 CPU 在进行转换。

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