Split elements of `source` based on `sep` into a `SparseTensor`.
Let N be the size of source (typically N will be the batch size). Split each element of `source` based on `sep` and return a `SparseTensor` containing the split tokens. Empty tokens are ignored.
For example, N = 2, source[0] is 'hello world' and source[1] is 'a b c', then the output will be
st.indices = [0, 0;
0, 1;
1, 0;
1, 1;
1, 2]
st.shape = [2, 3]
st.values = ['hello', 'world', 'a', 'b', 'c']
If `sep` is given, consecutive delimiters are not grouped together and are
deemed to delimit empty strings. For example, source 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 startor end if the string has
leading or trailing whitespace.
Note that the above mentioned behavior matches python's str.split.
Nested Classes
class | StringSplit.Options | Optional attributes for StringSplit
|
Constants
String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
static StringSplit | |
Output<TInt64> |
indices()
|
static StringSplit.Options |
maxsplit(Long maxsplit)
|
Output<TInt64> |
shape()
|
Output<TString> |
values()
|
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public static StringSplit create (Scope scope, Operand<TString> input, Operand<TString> sep, Options... options)
Factory method to create a class wrapping a new StringSplit operation.
Parameters
scope | current scope |
---|---|
input | `1-D` string `Tensor`, the strings to split. |
sep | `0-D` string `Tensor`, the delimiter character. |
options | carries optional attributes values |
Returns
- a new instance of StringSplit
public static StringSplit.Options maxsplit (Long maxsplit)
Parameters
maxsplit | An `int`. If `maxsplit > 0`, limit of the split of the result. |
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