code: def string_to_number(input, out_type=dtypes.float32, name=None):
      r"""Converts each string in the input Tensor to the specified numeric type.
  
      (Note that int32 overflow results in an error while float overflow
      results in a rounded value.)
  
      Examples:
  
      >>> tf.strings.to_number("1.55")
      <tf.Tensor: shape=(), dtype=float32, numpy=1.55>
      >>> tf.strings.to_number("3", tf.int32)
      <tf.Tensor: shape=(), dtype=int32, numpy=3>
  
      Args:
        input: A `Tensor` of type `string`.
        out_type: An optional `tf.DType` from: `tf.float32, tf.float64, tf.int32,
          tf.int64`. Defaults to `tf.float32`.
          The numeric type to interpret each string in `string_tensor` as.
        name: A name for the operation (optional).
  
      Returns:
        A `Tensor` of type `out_type`.
      """
      return gen_parsing_ops.string_to_number(input, out_type, name)
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_parsing_ops
  from tensorflow.python.ops import gen_string_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.gen_string_ops import *
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 14 for calling a global function with example usage: string_to_number(input, out_type, name) and returns: gen_parsing_ops