The tensor

What is a tensor?

A  tensor is one structure which is needed and used from many AI environments.

Basically the tensor is a kind of a 4 dimensional matrix, containing parameters for 

dimensions and data itself. The 'data' has the information used  from the environment, 

this information may be color of a pixel, velocity of a motor, position of some object. 

Generally it is one or more junks of bytes. The order of this data contained in the tensor 

usually is a structure described through some matrices and vectors. 

From the software point of view, I am using tensor in my AI developments as a class 

described below

n is the number of samples. This is the size of the  vector containing  the base data. For example, the  base data is one picture, usually denoted by one array  of 3, 4 pixel information (r, g, b, a). Sometimes named      as ‘channels’. Form the software point of view defined      as std::vector<Array of data..> k is describing the number of the filters. Filters are      quadratic groups of data within one array of data.      For example one filter may be a quadratic small array      of our pixels (3x3), (4x4), (30x30),(...) nr is the number of rows contained in only one array of      data, For examples 30 rows are there. nc is the number of columns containing the data  size is the total size of the Tensor. It may be calculated  as the following product: size = n x nr x nc   For example n= 2, nr = 3, nc = 4 => size = 24