What are tensors in PyTorch?

In PyTorch, tensors are a data structure similar to multi-dimensional arrays that can store and manipulate multi-dimensional data. Tensors in PyTorch are the main data type used to represent inputs, outputs, and parameters of neural networks. Tensors can have any number of dimensions, such as scalars (0-dimensional tensors), vectors (1-dimensional tensors), matrices (2-dimensional tensors), and so on. Tensors in PyTorch are similar to arrays in NumPy, but can be accelerated for computation on a GPU. PyTorch provides a wide range of tensor operations and functions to facilitate data processing, mathematical operations, and building neural network models.