# tf.raw_ops.SaveSlices

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Saves input tensors slices to disk.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.raw_ops.SaveSlices(
        filename, tensor_names, shapes_and_slices, data, name=None
    )

This is like `Save` except that tensors can be listed in the saved file as being
a slice of a larger tensor. `shapes_and_slices` specifies the shape of the
larger tensor and the slice that this tensor covers. `shapes_and_slices` must
have as many elements as `tensor_names`.

Elements of the `shapes_and_slices` input must either be:

- The empty string, in which case the corresponding tensor is saved normally.
- A string of the form `dim0 dim1 ... dimN-1 slice-spec` where the `dimI` are the dimensions of the larger tensor and `slice-spec` specifies what part is covered by the tensor to save.

`slice-spec` itself is a `:`-separated list: `slice0:slice1:...:sliceN-1`
where each `sliceI` is either:

- The string `-` meaning that the slice covers all indices of this dimension
- `start,length` where `start` and `length` are integers. In that case the slice covers `length` indices starting at `start`.

See also `Save`.

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| ## Args ||
|---|---|
| `filename` | A `Tensor` of type `string`. Must have a single element. The name of the file to which we write the tensor. |
| `tensor_names` | A `Tensor` of type `string`. Shape `[N]`. The names of the tensors to be saved. |
| `shapes_and_slices` | A `Tensor` of type `string`. Shape `[N]`. The shapes and slice specifications to use when saving the tensors. |
| `data` | A list of `Tensor` objects. `N` tensors to save. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| The created Operation. ||

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