# tf.raw_ops.Unpack

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Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.raw_ops.Unpack(
        value, num, axis=0, name=None
    )

Unpacks `num` tensors from `value` by chipping it along the `axis` dimension.
For example, given a tensor of shape `(A, B, C, D)`;

If `axis == 0` then the i'th tensor in `output` is the slice `value[i, :, :, :]`
and each tensor in `output` will have shape `(B, C, D)`. (Note that the
dimension unpacked along is gone, unlike `split`).

If `axis == 1` then the i'th tensor in `output` is the slice `value[:, i, :, :]`
and each tensor in `output` will have shape `(A, C, D)`.
Etc.

This is the opposite of `pack`.

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| ## Args ||
|---|---|
| `value` | A `Tensor`. 1-D or higher, with `axis` dimension size equal to `num`. |
| `num` | An `int` that is `>= 0`. |
| `axis` | An optional `int`. Defaults to `0`. Dimension along which to unpack. Negative values wrap around, so the valid range is `[-R, R)`. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A list of `num` `Tensor` objects with the same type as `value`. ||

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