tf.ones_like
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Creates a tensor of all ones that has the same shape as the input.
tf.ones_like(
input, dtype=None, name=None, layout=None
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
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.
Args |
|---|
input
|
A Tensor.
|
dtype
|
A type for the returned Tensor. Must be float16, float32,
float64, int8, uint8, int16, uint16, int32, int64,
complex64, complex128, bool or string.
|
name
|
A name for the operation (optional).
|
layout
|
Optional, tf.experimental.dtensor.Layout. If provided, the result
is a DTensor with the
provided layout.
|
Returns |
|---|
A Tensor with all elements set to one.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.ones_like\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/array_ops.py#L2815-L2866) |\n\nCreates a tensor of all ones that has the same shape as the input. \n\n tf.ones_like(\n input, dtype=None, name=None, layout=None\n )\n\n### Used in the notebooks\n\n| Used in the guide | Used in the tutorials |\n|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [Extension types](https://www.tensorflow.org/guide/extension_type) - [Validating correctness \\& numerical equivalence](https://www.tensorflow.org/guide/migrate/validate_correctness) | - [CycleGAN](https://www.tensorflow.org/tutorials/generative/cyclegan) - [Deep Convolutional Generative Adversarial Network](https://www.tensorflow.org/tutorials/generative/dcgan) - [pix2pix: Image-to-image translation with a conditional GAN](https://www.tensorflow.org/tutorials/generative/pix2pix) - [Multilevel Modeling Primer in TensorFlow Probability](https://www.tensorflow.org/probability/examples/Multilevel_Modeling_Primer) - [Research tools](https://www.tensorflow.org/quantum/tutorials/research_tools) |\n\nSee also [`tf.ones`](../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 tensor = tf.constant([[1, 2, 3], [4, 5, 6]])\n 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`](../tf/experimental/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`](../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"]]
View source on GitHub