Why does dim=1 return row indices in torch.argmax?
I am working on argmax function of PyTorch which is defined as:

torch.argmax(input, dim=None, keepdim=False)


Consider an example 

a = torch.randn(4, 4)
print(a)
print(torch.argmax(a, dim=1))


Here when I use dim=1 instead of searching column vectors, the function searches for row vectors as shown below.

print(a) :   
tensor([[-1.7739,  0.8073,  0.0472, -0.4084],  
        [ 0.6378,  0.6575, -1.2970, -0.0625],  
        [ 1.7970, -1.3463,  0.9011, -0.8704],  
        [ 1.5639,  0.7123,  0.0385,  1.8410]])  

print(torch.argmax(a, dim=1))  
tensor([1, 1, 0, 3])


As far as my assumption goes dim = 0 represents rows and dim =1 represent columns. 

It's time to correctly understand how the axis or dim argument work in PyTorch:





The following example should make sense once you comprehend the above picture:


    |
    v
  dim-0  ---&gt; -----&gt; dim-1 ------&gt; -----&gt; --------&gt; dim-1
    |   [[-1.7739,  0.8073,  0.0472, -0.4084],
    v    [ 0.6378,  0.6575, -1.2970, -0.0625],
    |    [ 1.7970, -1.3463,  0.9011, -0.8704],
    v    [ 1.5639,  0.7123,  0.0385,  1.8410]]
    |
    v



# argmax (indices where max values are present) along dimension-1
In [215]: torch.argmax(a, dim=1)
Out[215]: tensor([1, 1, 0, 3])




Note: dim (short for 'dimension') is the torch equivalent of 'axis' in NumPy.
