# 0維Tensor：也就是一個標量（Scalar）,它沒有維度，
# 1維Tensor：也稱作向量（Vector),它有一個維度
# 2維Tensor：也稱作矩陣（Matrix）,它有兩個維度
# 3維Tensor：也叫高維Tensor(>=3), 它有3個維度可以想象為一個數據立方體

import torch

x = torch.tensor(1)
print(x.shape, x.size(), x.dim())

x = torch.tensor([1])
print(x.shape, x.size(), x.dim())

x = torch.tensor([1, 2, 3])
print(x.shape, x.size(), x.dim())

x = torch.tensor([[1, 2, 3], [4, 5, 6]])
print(x.shape, x.size(), x.dim())

x = torch.tensor([[1]])
print(x.shape, x.size(), x.dim())

x = torch.tensor([[1, 2, 3]])
print(x.shape, x.size(), x.dim())

x = torch.tensor([[1], [1], [1]])
print(x.shape, x.size(), x.dim())

x = torch.tensor([[[1]]])
print(x.shape, x.size(), x.dim())
x = torch.tensor([[[1, 2, -1], [3, 4, -1]], [[5, 6, -1], [7, 8, -1]]])
print(x.shape, x.size(), x.dim())

'''
torch.Size([]) torch.Size([]) 0
torch.Size([1]) torch.Size([1]) 1
torch.Size([3]) torch.Size([3]) 1
torch.Size([2, 3]) torch.Size([2, 3]) 2
torch.Size([1, 1]) torch.Size([1, 1]) 2
torch.Size([1, 3]) torch.Size([1, 3]) 2
torch.Size([3, 1]) torch.Size([3, 1]) 2
torch.Size([1, 1, 1]) torch.Size([1, 1, 1]) 3
torch.Size([2, 2, 3]) torch.Size([2, 2, 3]) 3
'''