c56dc1933bd601a4630e963d4f0d3142fdc9c0d9,tutorials/mnist.py,,loss,#,82

Before Change

  cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits,
                                                          onehot_labels,
                                                          name="xentropy")
  loss = tf.reduce_mean(cross_entropy, name="xentropy_mean")
  return loss


def training(loss, learning_rate):

After Change

    cross_entropy = tf.nn.softmax_cross_entropy_with_logits(
        logits, onehot_labels, name="xentropy"
    )
    return tf.reduce_mean(cross_entropy, name="xentropy_mean")


def convert_labels_to_onehot(labels):
    

Instances