62cea7fcfcc9e20b784e08bddce5dc69b9578ef4,tensorforce/core/memories/replay.py,Replay,tf_retrieve_sequences,#Replay#Any#Any#,125

Before Change

        // ???????
        // sequence_indices = [tf.range(start=indices[n], limit=(indices[n] + sequence_length)) for k in range(n)]
        // sequence_indices = [indices[k: k + sequence_length] for k in tf.unstack(value=tf.range(start=0, limit=n), num=n)]
        sequence_indices = tf.expand_dims(input=tf.range(start=0, limit=n), axis=1) + tf.expand_dims(input=tf.constant(value=list(range(sequence_length))), axis=0)
        sequence_indices = tf.reshape(tensor=sequence_indices, shape=(n * sequence_length,))
        // sequence_indices = tf.concat(values=sequence_indices, axis=0)  // tf.stack !!!!!
        terminal = tf.gather(params=self.memories["terminal"], indices=indices)
        sequence_indices = tf.boolean_mask(tensor=sequence_indices, mask=tf.logical_not(x=terminal))

After Change

        // sequence_indices = [tf.range(start=indices[n], limit=(indices[n] + sequence_length)) for k in range(n)]
        // sequence_indices = [indices[k: k + sequence_length] for k in tf.unstack(value=tf.range(start=0, limit=n), num=n)]
        sequence_indices = tf.expand_dims(input=tf.range(start=0, limit=n), axis=1)
        sequence_indices += tf.expand_dims(input=tf.range(start=0, limit=sequence_length), axis=0)
        sequence_indices = tf.reshape(tensor=sequence_indices, shape=(n * sequence_length,))
        // sequence_indices = tf.concat(values=sequence_indices, axis=0)  // tf.stack !!!!!
        terminal = tf.gather(params=self.memories["terminal"], indices=indices)
        sequence_indices = tf.boolean_mask(tensor=sequence_indices, mask=tf.logical_not(x=terminal))

Instances