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Split elements of input based on sep into a RaggedTensor.
tf.strings.split(
input, sep=None, maxsplit=-1, name=None
)
Let N be the size of input (typically N will be the batch size). Split each
element of input based on sep and return a RaggedTensor containing the
split tokens. Empty tokens are ignored.
Example:
tf.strings.split('hello world').numpy()array([b'hello', b'world'], dtype=object)tf.strings.split(['hello world', 'a b c'])<tf.RaggedTensor [[b'hello', b'world'], [b'a', b'b', b'c']]>
If sep is given, consecutive delimiters are not grouped together and are
deemed to delimit empty strings. For example, input of "1<>2<><>3" and
sep of "<>" returns ["1", "2", "", "3"]. If sep is None or an empty
string, consecutive whitespace are regarded as a single separator, and the
result will contain no empty strings at the start or end if the string has
leading or trailing whitespace.
Note that the above mentioned behavior matches python's str.split.
Raises | |
|---|---|
ValueError
|
If sep is not a string. |
Returns | |
|---|---|
A RaggedTensor of rank N+1, the strings split according to the
delimiter.
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View source on GitHub