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
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)
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TensorFlow 1 version
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