introduction to pytorch tensor is nothing but multi-dimensional array of objects of the same type (usually floating-point numbersalthough bit of an oversimplificationit' fair to say that at lower level of abstractionall computation in pytorch is tensors and operations over tensors thusin order for you to be fluent with pytorchit is essential that you develop an intuitive understanding of tensors and the operations over them it must also be noted that this introduction to tensors and their operations is by no means completeyou should refer to the pytorch documentation for specific use cases howeverit' also essential to point out that this covers all the conceptual aspects of tensors and their operations you should try out the examples in this section in python terminal (jupyter notebook is recommended the best way to internalize this material is to read about the concepttype out the source codeand see it execute figure - - dimensional tensor tensor is generalized way of representing scalarvectorand matrices tensor can be defined as an -dimensional matrix -dimensional tensor ( single numberis called scalar (figure - ) -dimensional tensor is called vectora -dimensional tensor is called matrix -dimensional tensor is also called cubeetc the dimension of matrix is also called the rank of tensor