tf.raw_ops.ConcatOffset
Stay organized with collections
Save and categorize content based on your preferences.
Computes offsets of concat inputs within its output.
tf.raw_ops.ConcatOffset(
concat_dim, shape, name=None
)
For example:
x = [2, 2, 7]
y = [2, 3, 7]
z = [2, 9, 7]
offsets = concat_offset(1, [x, y, z])
[list(off.numpy()) for off in offsets]
[[0, 0, 0], [0, 2, 0], [0, 5, 0]]
This is typically used by gradient computations for a concat operation.
Args |
concat_dim
|
A Tensor of type int32 .
The dimension along which to concatenate.
|
shape
|
A list of at least 2 Tensor objects with type int32 .
The N int32 vectors representing shape of tensors being concatenated.
|
name
|
A name for the operation (optional).
|
Returns |
A list with the same length as shape of Tensor objects with type int32 .
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.ConcatOffset\n\n\u003cbr /\u003e\n\nComputes offsets of concat inputs within its output.\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.ConcatOffset`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/ConcatOffset)\n\n\u003cbr /\u003e\n\n tf.raw_ops.ConcatOffset(\n concat_dim, shape, name=None\n )\n\n#### For example:\n\n x = [2, 2, 7]\n y = [2, 3, 7]\n z = [2, 9, 7]\n offsets = concat_offset(1, [x, y, z])\n [list(off.numpy()) for off in offsets]\n [[0, 0, 0], [0, 2, 0], [0, 5, 0]]\n\nThis is typically used by gradient computations for a concat operation.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------|----------------------------------------------------------------------------------------------------------------------------------|\n| `concat_dim` | A `Tensor` of type `int32`. The dimension along which to concatenate. |\n| `shape` | A list of at least 2 `Tensor` objects with type `int32`. The `N` int32 vectors representing shape of tensors being concatenated. |\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 with the same length as `shape` of `Tensor` objects with type `int32`. ||\n\n\u003cbr /\u003e"]]