code: def _get_encoder_hparams(self):
      hparams = transformer.transformer_small()
      hparams.add_hparam(
          "encoder_layer_list", layers.ENCODER_LAYERS.get_layer_names()
      )
      hparams.add_hparam(
          "encoder_output_dim_list",
          [32] + [64] * (len(hparams.encoder_layer_list) - 2) + [32],
      )
      hparams.add_hparam(
          "encoder_activation_list",
          ["none"] + ["relu"] * (len(hparams.encoder_layer_list) - 1),
      )
      hparams.add_hparam(
          "encoder_norm_list",
          ["none"]
          + ["layer_norm"] * (len(hparams.encoder_layer_list) - 1),
      )
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  from tensor2tensor.data_generators import problem_hparams
  from tensor2tensor.layers import common_attention
  from tensor2tensor.models import transformer
  from tensor2tensor.models.neural_architecture_search import nas_layers
  from tensor2tensor.models.neural_architecture_search import nas_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 2 for calling the NasSeq2SeqTest obj's underlying member method code with example usage: obj._get_encoder_hparams() and returns: hparams