What is the Tensor in Torch?

In Torch, a Tensor is a multi-dimensional array data structure, similar to arrays in NumPy. It is the most basic data type in Torch and can be used to represent vectors, matrices, or higher-dimensional data. Tensors support various mathematical operations such as addition, subtraction, multiplication, division, as well as broadcasting, indexing, and slicing. Widely used in deep learning, Tensors are used to store model parameters, input data, and compute intermediate results. Tensors can run on both CPU and GPU, providing efficient tensor operations, making them a crucial data structure in Torch.