code: def build_classification_head(
      inputs: tf.Tensor, l2: float = 0.0
  ) -> tf.Tensor:
      """Returns an output head tensor configured for classification.
  
      In the future, this can be extended for regression, or with different params
      for different heads.
  
      Args:
        inputs: The backbone output tensor; used as the input to the head.
        l2: The l2 regularization factor used in `tf.keras.layers.Dense` layers.
  
      Returns:
        A tensor representing the output of the given head.
      """
      l2_regularizer = tf.keras.regularizers.L2(l2) if l2 else None
      head = tf.keras.layers.Dense(
          dv_constants.NUM_CLASSES,
          activation="softmax",
          dtype=tf.float32,
          name="classification",
          kernel_regularizer=l2_regularizer,
      )
      return head(inputs)
  
imports: import os
  import tempfile
  from typing import Callable, Optional, Tuple, Type, Union
  from absl import logging
  import ml_collections
  import numpy
  import tensorflow
  import tensorflow_addons
  from deepvariant import dv_constants
  from deepvariant import dv_utils
label_desc: Use image node_id 1 for calling a global function with example usage: build_classification_head(inputs, l2) and returns: head