introduction to pytorch pytorch is very rich library that provides numerous functions that enable building blocks for deep learning this looks briefly at some of the functionalities pytorch provides for creating tensors and performing data munging operationslinear algebraand mathematical operations to beginlet' explore the multitude of ways to construct tensors the most basic way is to construct tensor using lists in python the following exercise will demonstrate an array of tensor operations that are commonly used in building deep learning applications to help you engage the flow betterthe codes and output have been maintained the notebook style (interactive flowinput output next input next output and so onc reating tensors in listing - we have constructed -dimensional tensor using nested lists we store this tensor as variable and then look at its shape listing - creating -dimensional tensor in [ ]import torch torch tensor([[ ],[ ]]out[ ]tensor([[ ][ ]]the shape indicates the dimensions of the tensor and the total number of dimensions that would be used to infer the rank of the tensor in listing - dimension [ , would be inferred as rank listing - explores the shape of tensor