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.
 |