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meridian.backend.ones_like
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Creates a tensor of all ones that has the same shape as the input.
meridian
.
backend
.
ones_like
(
input
,
dtype
=
None
,
name
=
None
,
layout
=
None
)
See also tf.ones
.
Given a single tensor ( tensor
), this operation returns a tensor of the
same type and shape as tensor
with all elements set to 1. Optionally,
you can use dtype
to specify a new type for the returned tensor.
For example:
>>>
tensor
=
tf
.
constant
([[
1
,
2
,
3
],
[
4
,
5
,
6
]])
>>>
tf
.
ones_like
(
tensor
)
< tf
.
Tensor
:
shape
=
(
2
,
3
),
dtype
=
int32
,
numpy
=
array
([[
1
,
1
,
1
],
[
1
,
1
,
1
]],
dtype
=
int32
)
>
Note that the layout of the input tensor is not preserved if the op
is used inside tf.function. To obtain a tensor with the same layout as the
input, chain the returned value to a dtensor.relayout_like
.
A type for the returned Tensor
. Must be float16
, float32
, float64
, int8
, uint8
, int16
, uint16
, int32
, int64
, complex64
, complex128
, bool
or string
.
A name for the operation (optional).
Optional, tf.experimental.dtensor.Layout
. If provided, the result
is a DTensor
with the
provided layout.
A Tensor
with all elements set to one.
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, 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.
Last updated 2025-08-16 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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-16 UTC."],[],[],null,["# meridian.backend.ones_like\n\n\u003cbr /\u003e\n\nCreates a tensor of all ones that has the same shape as the input. \n\n meridian.backend.ones_like(\n input, dtype=None, name=None, layout=None\n )\n\nSee also `tf.ones`.\n\nGiven a single tensor (`tensor`), this operation returns a tensor of the\nsame type and shape as `tensor` with all elements set to 1. Optionally,\nyou can use `dtype` to specify a new type for the returned tensor.\n\n#### For example:\n\n \u003e\u003e\u003e tensor = tf.constant([[1, 2, 3], [4, 5, 6]])\n \u003e\u003e\u003e tf.ones_like(tensor)\n \u003ctf.Tensor: shape=(2, 3), dtype=int32, numpy=\n array([[1, 1, 1],\n [1, 1, 1]], dtype=int32)\u003e\n\nNote that the layout of the input tensor is not preserved if the op\nis used inside tf.function. To obtain a tensor with the same layout as the\ninput, chain the returned value to a `dtensor.relayout_like`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input` | A `Tensor`. |\n| `dtype` | A type for the returned `Tensor`. Must be `float16`, `float32`, `float64`, `int8`, `uint8`, `int16`, `uint16`, `int32`, `int64`, `complex64`, `complex128`, `bool` or `string`. |\n| `name` | A name for the operation (optional). |\n| `layout` | Optional, `tf.experimental.dtensor.Layout`. If provided, the result is a [DTensor](https://www.tensorflow.org/guide/dtensor_overview) with the provided layout. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` with all elements set to one. ||\n\n\u003cbr /\u003e"]]
