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)