The following code is from lession 5.
I don’t understand why forward function that returns of type
[torch.cuda.FloatTensor of size 32 (GPU 0)] based on the input mini batch users, and movies size 64. It contains only 32 distinct values. I am not sure what the value represents.
I am trying to visualize in the callab_filter.xlsx. If I choose 32 users, and 32 movies, I will get cells size 32 x 32. How does the forward function related to the spreadsheet? Shouldn’t the output be Tensor of size 32 x 32 in the forward function?
class EmbeddingDot(nn.Module): def __init__(self, n_users, n_movies): super().__init__() self.u = nn.Embedding(n_users, n_factors) self.m = nn.Embedding(n_movies, n_factors) self.u.weight.data.uniform_(0,0.05) self.m.weight.data.uniform_(0,0.05) def forward(self, cats, conts): users,movies = cats[:,0],cats[:,1] u,m = self.u(users),self.m(movies) return (u*m).sum(1)