tf.strings.unicode_encode

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
)

Used in the notebooks

Used in the guide

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

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 code point sequence. Can be "UTF-8", "UTF-16-BE", or "UTF-32-BE".
errors Specifies the response when a code point that is not a Unicode scalar value is encountered (optional). One of:

  * `'replace'`: Replace non-scalar-value with the
    `replacement_char`. (default)
  * `'ignore'`: Skip non-scalar-value .
  * `'strict'`: Raise an exception for any non-scalar-value.

replacement_char The replacement character to be used in place of any invalid input when errors='replace'. Any Unicode scalar value may be used. The default value is the default Unicode replacement character which is 0xFFFD (U+65533).
name A name for the operation (optional).

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)