code: def get_dtype(hparams):
      if hparams.activation_dtype == "float32":
          return tf.float32
      elif hparams.activation_dtype == "float64":
          return tf.float64
      elif hparams.activation_dtype == "bfloat16":
          return tf.bfloat16
      else:
          return None
  
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_layers
  from tensor2tensor.layers import transformer_glow_layers_ops
  from tensor2tensor.models.transformer import transformer_decoder_layer
  from tensor2tensor.models.transformer import transformer_encoder
  from tensor2tensor.models.transformer import transformer_prepare_encoder
  from tensor2tensor.utils import learning_rate
  from tensor2tensor.utils import mlperf_log
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 10 for calling a global function with example usage: get_dtype(hparams) and returns: tf, tf, tf, None