What is a PyTorch Tensor?
PyTorch tensors are the data structures that allow us to handle multi-dimensional arrays and perform mathematical operations on them. In other words, a PyTorch tensor is a multi-dimensional array that can hold data of a uniform data type. It is similar to NumPy arrays. These have different ranks that represent the scalars (0D), vectors (1D), matrices (2D), or higher-dimensional arrays (nD). They have various data types like floating-point numbers (float32, float64), integers (int32, int64), and others, which makes them flexible. Thus, tensors act as the backbone of the PyTorch model.
PyTorch Tensor vs NumPy Array
PyTorch and NumPy can help you create and manipulate multidimensional arrays. This article covers a detailed explanation of how the tensors differ from the NumPy arrays.