tf.compat.v1.string_split

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Split elements of source based on delimiter. (deprecated arguments)

tf.compat.v1.string_split(
    source, sep=None, skip_empty=True, delimiter=None, result_type='SparseTensor',
    name=None
)

Warning: SOME ARGUMENTS ARE DEPRECATED: (delimiter). They will be removed in a future version. Instructions for updating: delimiter is deprecated, please use sep instead.

Let N be the size of source (typically N will be the batch size). Split each element of source based on delimiter and return a SparseTensor or RaggedTensor containing the split tokens. Empty tokens are ignored.

If sep is an empty string, each element of the source is split into individual strings, each containing one byte. (This includes splitting multibyte sequences of UTF-8.) If delimiter contains multiple bytes, it is treated as a set of delimiters with each considered a potential split point.

Examples:

>>> print(tf.compat.v1.string_split(['hello world', 'a b c']))
SparseTensor(indices=tf.Tensor( [[0 0] [0 1] [1 0] [1 1] [1 2]], ...),
             values=tf.Tensor([b'hello' b'world' b'a' b'b' b'c'], ...),
             dense_shape=tf.Tensor([2 3], shape=(2,), dtype=int64))
>>> print(tf.compat.v1.string_split(['hello world', 'a b c'],
...     result_type="RaggedTensor"))
<tf.RaggedTensor [[b'hello', b'world'], [b'a', b'b', b'c']]>

Args:

Raises:

Returns:

A SparseTensor or RaggedTensor of rank 2, the strings split according to the delimiter. The first column of the indices corresponds to the row in source and the second column corresponds to the index of the split component in this row.