tf.strings.unicode_split

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Splits each string in input into a sequence of Unicode code points.

Aliases:

  • tf.compat.v1.strings.unicode_split
  • tf.compat.v2.strings.unicode_split
tf.strings.unicode_split(
    input,
    input_encoding,
    errors='replace',
    replacement_char=65533,
    name=None
)

result[i1...iN, j] is the substring of input[i1...iN] that encodes its jth character, when decoded using input_encoding.

Args:

  • input: An N dimensional potentially ragged string tensor with shape [D1...DN]. N must be statically known.
  • input_encoding: String name for the unicode encoding that should be used to decode each string.
  • errors: Specifies the response when an input string can't be converted using the indicated encoding. One of:
    • 'strict': Raise an exception for any illegal substrings.
    • 'replace': Replace illegal substrings with replacement_char.
    • 'ignore': Skip illegal substrings.
  • replacement_char: The replacement codepoint to be used in place of invalid substrings in input when errors='replace'.
  • name: A name for the operation (optional).

Returns:

A N+1 dimensional int32 tensor with shape [D1...DN, (num_chars)]. The returned tensor is a tf.Tensor if input is a scalar, or a tf.RaggedTensor otherwise.

Example:

  >>> input = [s.encode('utf8') for s in (u'G\xf6\xf6dnight', u'\U0001f60a')]
  >>> tf.strings.unicode_split(input, 'UTF-8').tolist()
  [['G', '\xc3\xb6', '\xc3\xb6', 'd', 'n', 'i', 'g', 'h', 't'],
   ['\xf0\x9f\x98\x8a']]

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