4b9d615d302d51a836ec0e5db0d31666c9b546e8,examples/iyyer_dan.py,,main,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,139

Before Change

            prev_best = n_correct

    print("Evaluating")
    eval_data = list(read_data(data_dir / "test"))
    n_correct = sum(y[model.predict(x).guess] == 0 for x, y in eval_data)
    print(n_correct / len(eval_data))
 

if __name__ == "__main__":

After Change

        avg_grad = 0.0
        for X_y in minibatch(train_data, bs=batch_size):
            batch = model.train(X_y)
            if str(batch.loss) == "nan":
                raise Exception(batch.gradient)
            train_loss += batch.loss
            avg_grad += batch.l1_gradient
            //avg_grad += sum(abs(g) for g in batch.gradient) / model.model.nr_weight
        n_correct = sum(y[model.predict(x).guess] == 0 for x, y in dev_data)

Instances