code: def regex_full_match(input, pattern, name=None):
      r"""Match elements of `input` with regex `pattern`.
  
      Args:
        input: string `Tensor`, the source strings to process.
        pattern: string or scalar string `Tensor`, regular expression to use,
          see more details at https://github.com/google/re2/wiki/Syntax
        name: Name of the op.
  
      Returns:
        bool `Tensor` of the same shape as `input` with match results.
      """
      if isinstance(pattern, util_compat.bytes_or_text_types):
          # When `pattern` is static through the life of the op we can
          # use a version which performs the expensive regex compilation once at
          # creation time.
          return gen_string_ops.static_regex_full_match(
              input=input, pattern=pattern, name=name
          )
      return gen_string_ops.regex_full_match(
          input=input, pattern=pattern, name=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 1 for calling a global function with example usage: regex_full_match(input, pattern, name) and returns: gen_string_ops, gen_string_ops