class_docstr: Tokenizes a tensor of UTF-8 strings on whitespaces.
class_docstr_tok: ["Tokenizes","a","tensor","of","UTF-8","strings","on","whitespaces","."]
docstr: Tokenizes a tensor of UTF-8 strings on whitespaces.
  
  The strings are split on ICU defined whitespace characters. These
  whitespace characters are dropped.
  
  Example:
  
  >>> WhitespaceTokenizer().tokenize("small medium large")
  <tf.Tensor: shape=(3,), dtype=string, numpy=array([b'small', b'medium',
  b'large'], dtype=object)>
  
  Args:
    input: A `RaggedTensor` or `Tensor` of UTF-8 strings with any shape.
  
  Returns:
    A `RaggedTensor` of tokenized text. The returned shape is the shape of the
    input tensor with an added ragged dimension for tokens of each string.
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code: def tokenize(self, input):  # pylint: disable=redefined-builtin
      """Tokenizes a tensor of UTF-8 strings on whitespaces.
  
      The strings are split on ICU defined whitespace characters. These
      whitespace characters are dropped.
  
      Example:
  
      >>> WhitespaceTokenizer().tokenize("small medium large")
      <tf.Tensor: shape=(3,), dtype=string, numpy=array([b'small', b'medium',
      b'large'], dtype=object)>
  
      Args:
        input: A `RaggedTensor` or `Tensor` of UTF-8 strings with any shape.
  
      Returns:
        A `RaggedTensor` of tokenized text. The returned shape is the shape of the
        input tensor with an added ragged dimension for tokens of each string.
      """
      (tokens, _, _) = self.tokenize_with_offsets(input)
      return tokens
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensorflow.python.eager import monitoring
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops.ragged import ragged_conversion_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
  from tensorflow_text.core.pybinds import pywrap_whitespace_tokenizer_config_builder
  from tensorflow_text.python.ops.tokenization import TokenizerWithOffsets
  from tensorflow.python.framework import load_library
  from tensorflow.python.platform import resource_loader
  from tensorflow.python.framework import load_library
  from tensorflow.python.platform import resource_loader
label_desc: Use image node_id 2 for calling the WhitespaceTokenizer obj's underlying member method code with example usage: obj.tokenize(input) and returns: tokens