2ef5a2c1e0ffc0fd8932debd03ab6a9e484957a2,cleverhans/utils_tf.py,,model_eval,#Any#Any#Any#Any#Any#Any#Any#Any#Any#,202

Before Change

                                 tf.argmax(predictions,
                                           axis=tf.rank(predictions) - 1))

    acc_value = tf.reduce_mean(tf.to_float(correct_preds))

    // Init result var
    accuracy = 0.0

After Change

            start = batch * args.batch_size
            end = min(len(X_test), start + args.batch_size)
            cur_batch_size = end - start
            X_cur[:cur_batch_size] = X_test[start:end]
            Y_cur[:cur_batch_size] = Y_test[start:end]

            // The last batch may be smaller than all others, so we need to
            // account for variable batch size here

Instances