Split a SparseTensor into num_split tensors along one dimension.
tf.raw_ops.SparseSplit(
    split_dim, indices, values, shape, num_split, name=None
)
If the shape[split_dim] is not an integer multiple of num_split. Slices
[0 : shape[split_dim] % num_split] gets one extra dimension.
For example, if split_dim = 1 and num_split = 2 and the input is
input_tensor = shape = [2, 7]
[    a   d e  ]
[b c          ]
Graphically the output tensors are:
output_tensor[0] = shape = [2, 4]
[    a  ]
[b c    ]
output_tensor[1] = shape = [2, 3]
[ d e  ]
[      ]
Args | 
split_dim
 | 
A Tensor of type int64.
0-D.  The dimension along which to split.  Must be in the range
[0, rank(shape)).
 | 
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.
output indices: A list of 1-D tensors represents the indices of the output
sparse tensors.
 | 
num_split
 | 
An int that is >= 1. The number of ways to split.
 | 
name
 | 
A name for the operation (optional).
 | 
Returns | 
A tuple of Tensor objects (output_indices, output_values, output_shape).
 | 
output_indices
 | 
A list of num_split Tensor objects with type int64.
 | 
output_values
 | 
A list of num_split Tensor objects with the same type as values.
 | 
output_shape
 | 
A list of num_split Tensor objects with type int64.
 |