# tf.raw_ops.SparseSlice

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Slice a `SparseTensor` based on the `start` and `size`.

#### View aliases


**Compat aliases for migration**

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

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

<br />

    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  ]
    [      ]

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<br />

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| ## 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). |

<br />

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| ## 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`. |

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