How to compute the cosine_similarity in pytorch for all rows in a matrix with respect to all rows in another matrix

Question

In pytorch, given that I have 2 matrixes how would I compute cosine similarity of all rows in each with all rows in the other.

For example

Given the input =

Answer 1

Adding eps for numerical stability base on benjaminplanche's answer:

def sim_matrix(a, b, eps=1e-8):
    """
    added eps for numerical stability
    """
    a_n, b_n = a.norm(dim=1)[:, None], b.norm(dim=1)[:, None]
    a_norm = a / torch.max(a_n, eps * torch.ones_like(a_n))
    b_norm = b / torch.max(b_n, eps * torch.ones_like(b_n))
    sim_mt = torch.mm(a_norm, b_norm.transpose(0, 1))
    return sim_mt