code: def _write_label_tensor(resolved_type, record, scalar):
      """Placeholder Docstring"""
      if resolved_type == "Int32":
          record.label["values"].int32_tensor.values.extend([scalar])
      elif resolved_type == "Float64":
          record.label["values"].float64_tensor.values.extend([scalar])
      elif resolved_type == "Float32":
          record.label["values"].float32_tensor.values.extend([scalar])
  
imports: from __future__ import absolute_import
  import io
  import logging
  import struct
  import sys
  import numpy
  from sagemaker.amazon.record_pb2 import Record
  from sagemaker.deprecations import deprecated_class
  from sagemaker.deserializers import SimpleBaseDeserializer
  from sagemaker.serializers import SimpleBaseSerializer
  from sagemaker.utils import DeferredError
label_desc: Use image node_id 2 for calling a global function with example usage: _write_label_tensor(resolved_type, record, scalar) without return types