Transformers, Pytorch, Machine Learning, Deep Dives, Data Science.
= torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(d_k) # we compute the weights of attention And this one, where we apply the normalized weights to the values : attention = torch.softmax(logits, dim=-1) output = torch.matmul(attention, value) # (batch_size, num_heads, sequence_length,