0ad33d606682537466f3430fc6d6ac7d47460f1a,beginner_source/nlp/word_embeddings_tutorial.py,,,#,237

Before Change

        // Step 4. Compute your loss function. (Again, Torch wants the target
        // word wrapped in a variable)
        loss = loss_function(log_probs, autograd.Variable(
            torch.LongTensor([word_to_ix[target]])))

        // Step 5. Do the backward pass and update the gradient
        loss.backward()

After Change

        // Step 4. Compute your loss function. (Again, Torch wants the target
        // word wrapped in a variable)
        loss = loss_function(log_probs, torch.tensor([word_to_ix[target]], dtype=torch.long))

        // Step 5. Do the backward pass and update the gradient
        loss.backward()

Instances