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 apply_forward_attention(
      self, alignment, alpha
  ):  # pylint: disable=no-self-use
      # forward attention
      fwd_shifted_alpha = tf.pad(
          alpha[:, :-1], ((0, 0), (1, 0)), constant_values=0.0
      )
      # compute transition potentials
      new_alpha = (
          (1 - 0.5) * alpha + 0.5 * fwd_shifted_alpha + 1e-8
      ) * alignment
      # renormalize attention weights
      new_alpha = new_alpha / tf.reduce_sum(
          new_alpha, axis=1, keepdims=True
      )
      return new_alpha
  
imports: import tensorflow
  from tensorflow import keras
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 7 for calling the Attention obj's underlying member method code with example usage: obj.apply_forward_attention(alignment, alpha) and returns: new_alpha