code: def _make_tensors_with_depth(inputs, depth=None):
      if depth is None:
          depth = tf.raw_ops.Placeholder(dtype=tf.int32, shape=[])
      else:
          depth = tf.constant(depth, dtype=tf.int32)
      return {
          "x": tf.one_hot(
              inputs["x"], depth=depth, dtype=inputs["x"].dtype
          )
      }
  
imports: import functools
  import os
  import tensorflow
  from tensorflow_transform import analyzers
  from tensorflow_transform import common
  from tensorflow_transform import graph_context
  from tensorflow_transform import mappers
  from tensorflow_transform import schema_inference
  from tensorflow_transform import tf2_utils
  from tensorflow_transform import test_case
  from tensorflow_transform.tf_metadata import schema_utils_legacy
  from tensorflow_transform.tf_metadata import schema_utils
  from google.protobuf import text_format
  import unittest
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 3 for calling a global function with example usage: _make_tensors_with_depth(inputs, depth) and returns: dict