477c6ffca3eeccac0402d3530886e16cb5a6d7f7,txtgen/losses/mle_losses.py,,average_sequence_softmax_cross_entropy,#Any#Any#Any#Any#Any#,88

Before Change

        losses = tf.nn.softmax_cross_entropy_with_logits(
            labels=labels, logits=logits)
        losses = _mask_sequences(losses, sequence_length, time_major)
        seq_length_sum = tf.to_float(tf.reduce_sum(sequence_length))
        loss = tf.reduce_sum(losses) / seq_length_sum
        return loss

After Change

        losses = tf.nn.softmax_cross_entropy_with_logits(
            labels=labels, logits=logits)
        losses = _mask_sequences(losses, sequence_length, time_major)
        loss = tf.reduce_sum(losses) / tf.to_float(tf.shape(labels)[0])
        return loss

Instances