tf.raw_ops.Diag
bookmark_borderbookmark
Stay organized with collections
Save and categorize content based on your preferences.
Returns a diagonal tensor with a given diagonal values.
View aliases
Compat aliases for migration
See
Migration guide for
more details.
tf.compat.v1.raw_ops.Diag
tf.raw_ops.Diag(
diagonal, name=None
)
Given a diagonal, this operation returns a tensor with the diagonal and
everything else padded with zeros. The diagonal is computed as follows:
Assume diagonal has dimensions [D1,..., Dk], then the output is a tensor of
rank 2k with dimensions [D1,..., Dk, D1,..., Dk] where:
output[i1,..., ik, i1,..., ik] = diagonal[i1, ..., ik] and 0 everywhere else.
For example:
# 'diagonal' is [1, 2, 3, 4]
tf.diag(diagonal) ==> [[1, 0, 0, 0]
[0, 2, 0, 0]
[0, 0, 3, 0]
[0, 0, 0, 4]]
Args |
|---|
diagonal
|
A Tensor. Must be one of the following types: bfloat16, half, float32, float64, int32, int64, complex64, complex128.
Rank k tensor where k is at most 1.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor. Has the same type as diagonal.
|
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 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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26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.Diag\n\n\u003cbr /\u003e\n\nReturns a diagonal tensor with a given diagonal values.\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.Diag`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Diag)\n\n\u003cbr /\u003e\n\n tf.raw_ops.Diag(\n diagonal, name=None\n )\n\nGiven a `diagonal`, this operation returns a tensor with the `diagonal` and\neverything else padded with zeros. The diagonal is computed as follows:\n\nAssume `diagonal` has dimensions \\[D1,..., Dk\\], then the output is a tensor of\nrank 2k with dimensions \\[D1,..., Dk, D1,..., Dk\\] where:\n\n`output[i1,..., ik, i1,..., ik] = diagonal[i1, ..., ik]` and 0 everywhere else.\n\n#### For example:\n\n # 'diagonal' is [1, 2, 3, 4]\n tf.diag(diagonal) ==\u003e [[1, 0, 0, 0]\n [0, 2, 0, 0]\n [0, 0, 3, 0]\n [0, 0, 0, 4]]\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `diagonal` | A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. Rank k tensor where k is at most 1. |\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 `Tensor`. Has the same type as `diagonal`. ||\n\n\u003cbr /\u003e"]]
