d4a2f656470e3190f8e877139455abcff1ad7cdb,rasa_core/policies/tf_utils.py,TimedNTM,__call__,#TimedNTM#Any#Any#Any#Any#,54

Before Change

                tf.reduce_sum(powed_probs, 1, keepdims=True) + 1e-32)

        // set probs for no intents and action_listens to zero
        if ignore_mask is not None:
            probs = tf.concat([tf.where(ignore_mask,
                                        tf.zeros_like(probs[:, :-1]),
                                        probs[:, :-1]),
                               probs[:, -1:]], 1)
        return probs, next_scores_state


def _compute_time_attention(attention_mechanism, attn_inputs, attention_state,

After Change

            // apply mask to scores
            if self._shift_weight is not None:
                // rearrange scores to make them continuous for convolution
                scores = tf.map_fn(self._rearrange_fn,
                                   [scores, mask], dtype=scores.dtype)
            else:
                scores = tf.where(mask > 0,
                                  scores, -self._inf * tf.ones_like(scores))

Instances