code: def aligned_local_1k():
      """Use local attention code, attend to full sequence.
  
      languagemodel_wiki_scramble1k50, 1gpu, 7k steps: log(ppl)_eval = 2.57
      7.5 steps/sec on P100
      8gpu (8x batch), 7k steps: log(ppl)_eval = 2.00
  
      Returns:
        a hparams object
      """
      hparams = aligned_local()
      hparams.local_attention_window = 1024
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import expert_utils
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 9 for calling a global function with example usage: aligned_local_1k() and returns: hparams