code: def activation_fn(features: tf1.Tensor, act_type: Text):
      """Customized non-linear activation type."""
      if act_type in ("silu", "swish"):
          return tf.keras.activations.swish(features)
      elif act_type == "swish_native":
          return features * tf.keras.activations.sigmoid(features)
      elif act_type == "hswish":
          return features * tf.nn.relu6(features + 3) / 6
      elif act_type == "relu":
          return tf.nn.relu(features)
      elif act_type == "relu6":
          return tf.nn.relu6(features)
      elif act_type == "mish":
          return features * tf.math.tanh(tf.math.softplus(features))
      elif act_type == "srelu":
          return srelu_fn(features)
      else:
          raise ValueError("Unsupported act_type {}".format(act_type))
  
imports: from typing import Text, Tuple, Union
  import tensorflow
  import argparse
  import tensorflow.compat.v1
  from enum import Enum
  from collections import namedtuple
  from tensorflow.python.eager import tape
  from tensorflow.python.tpu import tpu_function
label_desc: Use image node_id 5 for calling a global function with example usage: activation_fn(features, act_type) and returns: tf, unknown, unknown, tf, tf, unknown, srelu_fn