Packs a list of `N`

rank-`R`

tensors into one rank-`(R+1)`

tensor.

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.

# '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`

.

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). |

Returns | |
---|---|

A `Tensor` . Has the same type as `values` . |

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/Pack