tf.strings.unicode_encode

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

tf.strings.unicode_encode(
    input, output_encoding, errors='replace', replacement_char=65533, name=None
)

result[i1...iN] is the string formed by concatenating the Unicode codepoints input[1...iN, :], encoded using output_encoding.

Args:

• input: An N+1 dimensional potentially ragged integer tensor with shape [D1...DN, num_chars].
• output_encoding: Unicode encoding that should be used to encode each codepoint sequence. Can be "UTF-8", "UTF-16-BE", or "UTF-32-BE".
• errors: Specifies the response when an invalid codepoint is encountered (optional). One of: * 'replace': Replace invalid codepoint with the replacement_char. (default) * 'ignore': Skip invalid codepoints. * 'strict': Raise an exception for any invalid codepoint.
• replacement_char: The replacement character codepoint to be used in place of any invalid input when errors='replace'. Any valid unicode codepoint may be used. The default value is the default unicode replacement character which is 0xFFFD (U+65533).
• name: A name for the operation (optional).

Returns:

A N dimensional string tensor with shape [D1...DN].

Example:

>>> input = tf.ragged.constant(
...     [[71, 246, 246, 100, 110, 105, 103, 104, 116], [128522]])
>>> print(unicode_encode(input, 'UTF-8'))
tf.Tensor([b'G\xc3\xb6\xc3\xb6dnight' b'\xf0\x9f\x98\x8a'],
          shape=(2,), dtype=string)