# tf.raw_ops.SparseSplit

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Split a `SparseTensor` into `num_split` tensors along one dimension.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.SparseSplit`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseSplit)

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    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  ]
    [      ]

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| ## 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). |

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| ## 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`. |

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