1. An apparatus for processing a multi-dimensional tensor input, the apparatus comprising: multiple tensor index elements including a tensor index element for each of multiple nested loops used to traverse an N-dimensional tensor, wherein each tensor index element is a respective first hardware register configured to store an index value for a respective nested loop that is used to traverse a respective dimension of the N-dimensional tensor, and wherein the N-dimensional tensor includes data elements arranged across each of the N-dimensions and N is an integer that is equal to or greater than one, wherein each index value is a value that is updated each time an iteration of the respective nested loop for the index value is performed; multiple dimension multiplier elements, wherein each dimension multiplier element is a respective second hardware register configured to store a multiplier value for a respective dimension of the N-dimensional tensor, wherein each multiplier value is a constant value for the respective dimension of the N-dimensional tensor for the multiplier value and remains constant for each iteration of the respective nested loop that is used to traverse the respective dimension; and one or more hardware processors configured to execute one or more instructions of an instruction set executable by the one or more hardware processors, wherein execution of the one or more instructions causes the one or more hardware processors to perform operations comprising: determining memory addresses for locations in memory for storing data values for a sequence of data elements of the N-dimensional tensor by: for each iteration of an inner loop of the nested loops: determining, for each dimension of the N-dimensional tensor, a product of (i) the index value stored in the tensor index element for the nested loop that is used to traverse the dimension and (ii) the multiplier value for the dimension; and determining a memory address for a data element that corresponds to the iteration of the inner loop based on a sum of the product for each dimension of the N-dimensional tensor; and outputting data indicating the determined memory address for each data element in the sequence of data elements of the N-dimensional tensor.