Slice a SparseTensor
based on the start
and size
.
tf.raw_ops.SparseSlice(
indices, values, shape, start, size, name=None
)
For example, if the input is
input_tensor = shape = [2, 7]
[ a d e ]
[b c ]
Graphically the output tensors are:
sparse_slice([0, 0], [2, 4]) = shape = [2, 4]
[ a ]
[b c ]
sparse_slice([0, 4], [2, 3]) = shape = [2, 3]
[ d e ]
[ ]
Args |
indices
|
A Tensor of type int64 .
2-D tensor represents the indices of the sparse tensor.
|
values
|
A Tensor . 1-D tensor represents the values of the sparse tensor.
|
shape
|
A Tensor of type int64 .
1-D. tensor represents the shape of the sparse tensor.
|
start
|
A Tensor of type int64 .
1-D. tensor represents the start of the slice.
|
size
|
A Tensor of type int64 .
1-D. tensor represents the size of the slice.
output indices: A list of 1-D tensors represents the indices of the output
sparse tensors.
|
name
|
A name for the operation (optional).
|
Returns |
A tuple of Tensor objects (output_indices, output_values, output_shape).
|
output_indices
|
A Tensor of type int64 .
|
output_values
|
A Tensor . Has the same type as values .
|
output_shape
|
A Tensor of type int64 .
|