Splits each string in input into a sequence of Unicode code points.
tf.strings.unicode_split(
input,
input_encoding,
errors='replace',
replacement_char=65533,
name=None
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
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').to_list()
[[b'G', b'\xc3\xb6', b'\xc3\xb6', b'd', b'n', b'i', b'g', b'h', b't'],
[b'\xf0\x9f\x98\x8a']]