Decodes each string in input into a sequence of Unicode code points.
tf.strings.unicode_decode(
input, input_encoding, errors='replace', replacement_char=65533,
replace_control_characters=False, name=None
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
result[i1...iN, j] is the Unicode codepoint for the jth character in
input[i1...iN], 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'; and in place of C0 control
characters in input when replace_control_characters=True.
|
replace_control_characters
|
Whether to replace the C0 control characters
(U+0000 - U+001F) with the replacement_char.
|
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_decode(input, 'UTF-8').to_list()
[[71, 246, 246, 100, 110, 105, 103, 104, 116], [128522]]
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TensorFlow 1 version
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