# tf.raw_ops.Pack

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Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.raw_ops.Pack(
        values, axis=0, name=None
    )

Packs the `N` tensors in `values` into a tensor with rank one higher than each
tensor in `values`, by packing them along the `axis` dimension.
Given a list of tensors of shape `(A, B, C)`;

if `axis == 0` then the `output` tensor will have the shape `(N, A, B, C)`.
if `axis == 1` then the `output` tensor will have the shape `(A, N, B, C)`.
Etc.

#### For example:

    # 'x' is [1, 4]
    # 'y' is [2, 5]
    # 'z' is [3, 6]
    pack([x, y, z]) => [[1, 4], [2, 5], [3, 6]]  # Pack along first dim.
    pack([x, y, z], axis=1) => [[1, 2, 3], [4, 5, 6]]

This is the opposite of `unpack`.

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| ## Args ||
|---|---|
| `values` | A list of at least 1 `Tensor` objects with the same type. Must be of same shape and type. |
| `axis` | An optional `int`. Defaults to `0`. Dimension along which to pack. Negative values wrap around, so the valid range is `[-(R+1), R+1)`. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A `Tensor`. Has the same type as `values`. ||

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