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 for
more details.
tf.compat.v1.raw_ops.Unpack
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.
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).
|
Returns |
|---|
A list of num Tensor objects with the same type as value.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.Unpack\n\n\u003cbr /\u003e\n\nUnpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.Unpack`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Unpack)\n\n\u003cbr /\u003e\n\n tf.raw_ops.Unpack(\n value, num, axis=0, name=None\n )\n\nUnpacks `num` tensors from `value` by chipping it along the `axis` dimension.\nFor example, given a tensor of shape `(A, B, C, D)`;\n\nIf `axis == 0` then the i'th tensor in `output` is the slice `value[i, :, :, :]`\nand each tensor in `output` will have shape `(B, C, D)`. (Note that the\ndimension unpacked along is gone, unlike `split`).\n\nIf `axis == 1` then the i'th tensor in `output` is the slice `value[:, i, :, :]`\nand each tensor in `output` will have shape `(A, C, D)`.\nEtc.\n\nThis is the opposite of `pack`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|------------------------------------------------------------------------------------------------------------------------------------|\n| `value` | A `Tensor`. 1-D or higher, with `axis` dimension size equal to `num`. |\n| `num` | An `int` that is `\u003e= 0`. |\n| `axis` | An optional `int`. Defaults to `0`. Dimension along which to unpack. Negative values wrap around, so the valid range is `[-R, R)`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A list of `num` `Tensor` objects with the same type as `value`. ||\n\n\u003cbr /\u003e"]]
