code: def _make_converter(dtype):
      def _converter(x):
          return np.asarray(x).astype(dtype.as_numpy_dtype)
  
      return _converter
  
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.compiler.xla import xla
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import gen_data_flow_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import tensor_array_grad
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling a global function with example usage: _make_converter(dtype) and returns: _converter, np