dim, size, item and tolist in PyTorch

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*My post explains how to create and acceess a tensor.

dim() can get the number of dimensions from the 0D or more D tensor of zero or more elements as shown below:

*Memos:

• dim() can be used with a tensor but not with torch.
• ndim is the alias of dim().

import torch

my_tensor = torch.tensor(-3) # 0D tensor 
my_tensor.dim() # 0 
my_tensor = torch.tensor([-3, 7, -5, 2, 6, 3])
                         # 1D tensor my_tensor.dim() # 1 my_tensor[0].dim() # 0 
my_tensor = torch.tensor([[-3, 7, -5], [2, 6, 3], # 2D tensor                           [8, 0, -1], [4, 9, -6]])
my_tensor.dim() # 2 my_tensor[0].dim() # 1 my_tensor[0][0].dim() # 0 
my_tensor = torch.tensor([[[-3, 7], [-5, 2], [6, 3]], # 3D tensor                           [[8, 0], [-1, 4], [9, -6]],
                          [[5, -2], [-7, 9], [1, 1]], 
                          [[6, -4], [0, -9], [3, 5]]])
my_tensor.dim() # 3 my_tensor[0].dim() # 2 my_tensor[0][0].dim() # 1 my_tensor[0][0][0].ndim # 0 

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size() can get a size from the 0D or more D tensor of zero or more elements as shown below:

*Memos:

• size() can be used with a tensor but not with torch.
• The 1st argument with a tensor is dim(Optional-Type:int).
• shape is the alias of dim().

import torch

my_tensor = torch.tensor(-3) # 0D tensor 
my_tensor.size()
# torch.Size([]) 
my_tensor = torch.tensor([-3, 7, -5, 2, 6, 3]) # 1D tensor 
my_tensor.size()
# torch.Size([6]) 
my_tensor.size(dim=0)
my_tensor.size(dim=-1)
# 6 
my_tensor[0].size()
# torch.Size([]) 
my_tensor = torch.tensor([[-3, 7, -5], [2, 6, 3], # 2D tensor                           [8, 0, -1], [4, 9, -6]])
my_tensor.size()
# torch.Size([4, 3]) 
my_tensor.size(dim=0)
my_tensor.size(dim=-2)
# 4 
my_tensor.size(dim=1)
my_tensor.size(dim=-1)
my_tensor[0].size(dim=0)
my_tensor[0].size(dim=-1)
# 3 
my_tensor[0].size()
# torch.Size([3]) 
my_tensor[0][0].size()
# torch.Size([]) 
my_tensor = torch.tensor([[[-3, 7], [-5, 2], [6, 3]], # 3D tensor                           [[8, 0], [-1, 4], [9, -6]],
                          [[5, -2], [-7, 9], [1, 1]], 
                          [[6, -4], [0, -9], [3, 5]]])
my_tensor.size()
# torch.Size([4, 3, 2]) 
my_tensor.size(dim=0)
my_tensor.size(dim=-3)
# 4 
my_tensor.size(dim=1)
my_tensor.size(dim=-2)
my_tensor[0].size(dim=0)
my_tensor[0].size(dim=-2)
# 3 
my_tensor.size(dim=2)
my_tensor.size(dim=-1)
my_tensor[0].size(dim=1)
my_tensor[0].size(dim=-1)
my_tensor[0][0].size(dim=0)
my_tensor[0][0].size(dim=-1)
# 2 
my_tensor[0].size()
# torch.Size([3, 2]) 
my_tensor[0][0].size()
# torch.Size([2]) 
my_tensor[0][0][0].size()
# torch.Size([]) 

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item() can get a standard Python number from the 0D or more D tensor of only one element as shown below:

*Memos:

• item() can be used with a tensor but not with torch.
• A tensor must be a scalar.

import torch

my_tensor = torch.tensor(-3) # 0D tensor my_tensor = torch.tensor([-3]) # 1D tensor my_tensor = torch.tensor([[-3]]) # 2D tensor my_tensor = torch.tensor([[[-3]]]) # 3D tensor 
my_tensor.item()
# -3 

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tolist() can get a standard Python number or list from the 0D or more D tensor of zero or more elements as shown below. *tolist() can be used with a tensor but not with torch:

import torch

my_tensor = torch.tensor(-3) # 0D tensor 
my_tensor.tolist()
# -3 
my_tensor = torch.tensor([-3, 7, -5, 2, 6, 3]) # 1D tensor 
my_tensor.tolist()
# [-3, 7, -5, 2, 6, 3] 
my_tensor[0].tolist()
# -3 
my_tensor = torch.tensor([[-3, 7, -5], [2, 6, 3], # 2D tensor                           [8, 0, -1], [4, 9, -6]])
my_tensor.tolist()
# [[-3, 7, -5], [2, 6, 3], # [8, 0, -1], [4, 9, -6]] 
my_tensor[0].tolist()
# [-3, 7, -5] 
my_tensor[0][0].tolist()
# -3 
my_tensor = torch.tensor([[[-3, 7], [-5, 2], [6, 3]], # 3D tensor                           [[8, 0], [-1, 4], [9, -6]],
                          [[5, -2], [-7, 9], [1, 1]], 
                          [[6, -4], [0, -9], [3, 5]]])
my_tensor.tolist()
# [[[-3, 7], [-5, 2], [6, 3]], # [[8, 0], [-1, 4], [9, -6]], # [[5, -2], [-7, 9], [1, 1]], # [[6, -4], [0, -9], [3, 5]]] 
my_tensor[0].tolist()
# [[-3, 7], [-5, 2], [6, 3]] 
my_tensor[0][0].tolist()
# [-3, 7] 
my_tensor[0][0][0].tolist()
# -3 

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原文链接：dim, size, item and tolist in PyTorch