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 Tensorof typeint64.
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 Tensorof typeint64.
1-D. tensor represents the shape of the sparse tensor. | 
| start | A Tensorof typeint64.
1-D. tensor represents the start of the slice. | 
| size | A Tensorof typeint64.
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 Tensorobjects (output_indices, output_values, output_shape). | 
| output_indices | A Tensorof typeint64. | 
| output_values | A Tensor. Has the same type asvalues. | 
| output_shape | A Tensorof typeint64. |