code: def vqa_self_attention_feature_batch1024_big():
      """Big model."""
      hparams = vqa_self_attention_feature_batch1024()
      hparams.learning_rate_constant = 7e-4
      hparams.batch_size = 256
      hparams.hidden_size = 1024
      hparams.filter_size = 4096
      hparams.num_heads = 16
      hparams.layer_prepostprocess_dropout = 0.3
      hparams.attention_dropout = 0.3
      hparams.relu_dropout = 0.3
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import vqa_layers
  from tensor2tensor.models.research import vqa_attention
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  from tensorflow.contrib.layers.python.layers import utils
label_desc: Use image node_id 13 for calling a global function with example usage: vqa_self_attention_feature_batch1024_big() and returns: hparams