code: def get_kwargs(self, x_mask, hparams=None):
      if hparams is None:
          hparams = self.get_hparams()
      encoder_output = tf.random.uniform(
          (BATCH_SIZE, INPUT_LENGTH, HIDDEN_SIZE), dtype=DTYPE
      )
      encoder_decoder_attention_bias = tf.zeros(
          (BATCH_SIZE, 1, 1, INPUT_LENGTH), dtype=DTYPE
      )
      decoder_self_attention_bias = (
          1.0 - x_mask[:, tf.newaxis, tf.newaxis, :]
      )
      decoder_self_attention_bias *= -1e9
      kwargs = {
          "hparams": hparams,
          "encoder_output": encoder_output,
          "encoder_decoder_attention_bias": encoder_decoder_attention_bias,
          "decoder_self_attention_bias": decoder_self_attention_bias,
      }
      return kwargs
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tempfile
  from absl.testing import parameterized
  import numpy
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import transformer_glow_layers
  from tensor2tensor.layers import transformer_glow_layers_ops
  from tensor2tensor.models import transformer
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the TransformerGlowLayersTest obj's underlying member method code with example usage: obj.get_kwargs(x_mask, hparams) and returns: kwargs