tf.compat.v1.zeros_like
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Creates a tensor with all elements set to zero.
tf.compat.v1.zeros_like(
tensor, dtype=None, name=None, optimize=True
)
See also tf.zeros.
Given a single tensor (tensor), this operation returns a tensor of the
same type and shape as tensor with all elements set to zero. Optionally,
you can use dtype to specify a new type for the returned tensor.
Examples |
|---|
>>> tensor = tf.constant([[1, 2, 3], [4, 5, 6]])
>>> tf.zeros_like(tensor)
<tf.Tensor: shape=(2, 3), dtype=int32, numpy=
array([[0, 0, 0],
[0, 0, 0]], dtype=int32)>
tf.zeros_like(tensor, dtype=tf.float32)
<tf.Tensor: shape=(2, 3), dtype=float32, numpy=
array([[0., 0., 0.],
[0., 0., 0.]], dtype=float32)>
|
Args |
|---|
tensor
|
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. (optional)
|
name
|
A name for the operation (optional).
|
optimize
|
if True, attempt to statically determine the shape of tensor
and encode it as a constant. (optional, defaults to True)
|
Returns |
|---|
A Tensor with all elements set to zero.
|
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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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26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.compat.v1.zeros_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#L2627-L2664) |\n\nCreates a tensor with all elements set to zero. \n\n tf.compat.v1.zeros_like(\n tensor, dtype=None, name=None, optimize=True\n )\n\nSee also [`tf.zeros`](../../../tf/zeros).\n\nGiven a single tensor (`tensor`), this operation returns a tensor of the\nsame type and shape as `tensor` with all elements set to zero. Optionally,\nyou can use `dtype` to specify a new type for the returned tensor.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Examples -------- ||\n|---|---|\n| \u003cbr /\u003e \u003e\u003e\u003e tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) \u003e\u003e\u003e tf.zeros_like(tensor) \u003ctf.Tensor: shape=(2, 3), dtype=int32, numpy= array([[0, 0, 0], [0, 0, 0]], dtype=int32)\u003e tf.zeros_like(tensor, dtype=tf.float32) \u003ctf.Tensor: shape=(2, 3), dtype=float32, numpy= array([[0., 0., 0.], [0., 0., 0.]], dtype=float32)\u003e \u003cbr /\u003e ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `tensor` | 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`. (optional) |\n| `name` | A name for the operation (optional). |\n| `optimize` | if `True`, attempt to statically determine the shape of `tensor` and encode it as a constant. (optional, defaults to `True`) |\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 zero. ||\n\n\u003cbr /\u003e"]]
View source on GitHub