class_docstr: TODO: implement forward_attention
  TODO: location sensitive attention
  TODO: implement attention windowing 
class_docstr_tok: ["TODO",":","implement","forward_attention","TODO",":","location","sensitive","attention","TODO",":","implement","attention","windowing"]
code: def init_states(self, batch_size, value_length):
      states = []
      if self.use_loc_attn:
          attention_cum = tf.zeros([batch_size, value_length])
          attention_old = tf.zeros([batch_size, value_length])
          states = [attention_cum, attention_old]
      if self.use_forward_attn:
          alpha = tf.concat(
              [
                  tf.ones([batch_size, 1]),
                  tf.zeros([batch_size, value_length])[:, :-1] + 1e-7,
              ],
              1,
          )
          states.append(alpha)
      return tuple(states)
  
imports: import tensorflow
  from tensorflow import keras
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj.init_states(batch_size, value_length) and returns: tuple