A brief analysis of the understanding of functions

() Function understanding

(input, dim)  When used, it is equivalent to  (dim)

() function plays a role in dimensionality upscaling. Dim equals to represent one in which dimension is added. For example, the original size=([4]) of x, after (0), it becomes size=([1, 4]), and after (1) becomes size=([4, 1]), note that dim∈[-() - 1, () + 1]
For example

Enter a one-dimensional tensor, i.e. ()=1

# Enter:x = ([1, 2, 3, 4])  # ()=1
print(x)
print()
y = (0)
print(y)
print()  # At this time ()=2z = (1)
print(z)
print()  # at this time()=2

#Output:tensor([1, 2, 3, 4])
([4])
tensor([[1, 2, 3, 4]])
([1, 4])
tensor([[1],
        [2],
        [3],
        [4]])
([4, 1])

Enter a two-dimensional tensor, i.e. ()=2

# Enter:x = ([[1, 2, 3], [4, 5, 6]])  # ()=2
print(x)
print()
y = (0)
print(y)
print()  # At this time ()=3z = (1)
print(z)
print()  # at this time()=3

#Output:tensor([[1, 2, 3],
        [4, 5, 6]])
([2, 3])
tensor([[[1, 2, 3],
         [4, 5, 6]]])
([1, 2, 3])
tensor([[[1, 2, 3]],
        [[4, 5, 6]]])
([2, 1, 3])

Enter a four-dimensional tensor, i.e. ()=4

# Enter:x = ([[[[1, 2, 3], 
                    [4, 5, 6]],
                [[0, 2, 1], 
                 [1, 5, 2]]],
                [[[1, 2, 3], 
                  [4, 5, 6]],
                [[0, 2, 1], 
                 [1, 5, 2]]]])
print(x)
print()
y2 = (2)
print(y2)
print()
y3 = (3)
print(y3)
print()

#Output:tensor([[[[1, 2, 3],
          [4, 5, 6]],
         [[0, 2, 1],
          [1, 5, 2]]],
        [[[1, 2, 3],
          [4, 5, 6]],
         [[0, 2, 1],
          [1, 5, 2]]]])
([2, 2, 2, 3])
tensor([[[[[1, 2, 3],
           [4, 5, 6]]],
         [[[0, 2, 1],
           [1, 5, 2]]]],
        [[[[1, 2, 3],
           [4, 5, 6]]],
         [[[0, 2, 1],
           [1, 5, 2]]]]])
([2, 2, 1, 2, 3])
tensor([[[[[1, 2, 3]],
          [[4, 5, 6]]],
         [[[0, 2, 1]],
          [[1, 5, 2]]]],
        [[[[1, 2, 3]],
          [[4, 5, 6]]],
         [[[0, 2, 1]],
          [[1, 5, 2]]]]])
([2, 2, 2, 1, 3])

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