What is the concept of tensors in PyTorch?

In PyTorch, tensors are multi-dimensional arrays, similar to arrays in NumPy. Tensors in PyTorch can be stored on either the CPU or GPU, and support various mathematical operations. Tensors are the fundamental data structure in PyTorch used to represent the inputs, outputs, and parameters of neural networks. Tensors can be created using the torch.Tensor class, and various methods and operations from torch.Tensor can be used to perform operations and manipulations on tensors. Tensors in PyTorch support automatic differentiation, allowing for automatic gradient computation, making training neural networks simpler and more efficient.