w1 = torch.randn(D_input, D_hidden).type(dtype)

This line of code initializes a tensor `w1` with random values drawn from a normal distribution with a mean of 0 and standard deviation of 1. The tensor has dimensions `D_input` by `D_hidden`, where `D_input` is the number of input units and `D_hidden` is the number of hidden units in the neural network. The tensor is of type `dtype`, which is a variable that specifies the data type of the tensor (e.g., float32 or float64).