def string_split(source, delimiter=" "): # pylint: disable=invalid-name
"""Split elements of `source` based on `delimiter` into a `SparseTensor`.
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`
containing the splitted tokens. Empty tokens are ignored.
If `delimiter` 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.)
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']
Args:
source: `1-D` string `Output`, the strings to split.
delimiter: `0-D` string `Output`, the delimiter character, the string should
be length 0 or 1.
Returns:
A `SparseTensor` 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.
Raises:
ValueError: If delimiter is not a single-byte character.
"""
if isinstance(delimiter, six.string_types) and len(delimiter) > 1:
raise ValueError("delimiter must be a single byte-character, got %s" %
delimiter)
delimiter = ops.convert_to_tensor(delimiter, dtype=dtypes.string)
source = ops.convert_to_tensor(source, dtype=dtypes.string)
# pylint: disable=protected-access
indices, values, shape = gen_string_ops._string_split(source,
delimiter=delimiter)
# pylint: enable=protected-access
indices.set_shape([None, 2])
values.set_shape([None])
shape.set_shape([2])
return sparse_tensor.SparseTensor(indices, values, shape)
def string_split(source, delimiter=" "): # pylint: disable=invalid-name
"""Split elements of `source` based on `delimiter` into a `SparseTensor`.
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`
containing the splitted tokens. Empty tokens are ignored.
If `delimiter` 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.)
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']
Args:
source: `1-D` string `Tensor`, the strings to split.
delimiter: `0-D` string `Tensor`, the delimiter character, the string should
be length 0 or 1.
Returns:
A `SparseTensor` 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.
Raises:
ValueError: If delimiter is not a single-byte character.
"""
if isinstance(delimiter, six.string_types) and len(delimiter) > 1:
raise ValueError("delimiter must be a single byte-character, got %s" %
delimiter)
delimiter = ops.convert_to_tensor(delimiter, dtype=dtypes.string)
source = ops.convert_to_tensor(source, dtype=dtypes.string)
# pylint: disable=protected-access
indices, values, shape = gen_string_ops._string_split(
source, delimiter=delimiter)
# pylint: enable=protected-access
indices.set_shape([None, 2])
values.set_shape([None])
shape.set_shape([2])
return sparse_tensor.SparseTensor(indices, values, shape)
def string_split(source, delimiter=" ", skip_empty=True): # pylint: disable=invalid-name
"""Split elements of `source` based on `delimiter` into a `SparseTensor`.
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`
containing the split tokens. Empty tokens are ignored.
If `delimiter` 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.
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']
Args:
source: `1-D` string `Tensor`, the strings to split.
delimiter: `0-D` string `Tensor`, the delimiter character, the string should
be length 0 or 1.
skip_empty: A `bool`. If `True`, skip the empty strings from the result.
Raises:
ValueError: If delimiter is not a string.
Returns:
A `SparseTensor` 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.
"""
delimiter = ops.convert_to_tensor(delimiter, dtype=dtypes.string)
source = ops.convert_to_tensor(source, dtype=dtypes.string)
# pylint: disable=protected-access
indices, values, shape = gen_string_ops._string_split(
source, delimiter=delimiter, skip_empty=skip_empty)
# pylint: enable=protected-access
indices.set_shape([None, 2])
values.set_shape([None])
shape.set_shape([2])
return sparse_tensor.SparseTensor(indices, values, shape)
def string_split(source, delimiter=" ", skip_empty=True): # pylint: disable=invalid-name
"""Split elements of `source` based on `delimiter` into a `SparseTensor`.
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`
containing the split tokens. Empty tokens are ignored.
If `delimiter` 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.
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']
Args:
source: `1-D` string `Tensor`, the strings to split.
delimiter: `0-D` string `Tensor`, the delimiter character, the string should
be length 0 or 1.
skip_empty: A `bool`. If `True`, skip the empty strings from the result.
Raises:
ValueError: If delimiter is not a string.
Returns:
A `SparseTensor` 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.
"""
delimiter = ops.convert_to_tensor(delimiter, dtype=dtypes.string)
source = ops.convert_to_tensor(source, dtype=dtypes.string)
# pylint: disable=protected-access
indices, values, shape = gen_string_ops._string_split(
source, delimiter=delimiter, skip_empty=skip_empty)
# pylint: enable=protected-access
indices.set_shape([None, 2])
values.set_shape([None])
shape.set_shape([2])
return sparse_tensor.SparseTensor(indices, values, shape)
