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meridian.backend.divide_no_nan
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Computes a safe divide which returns 0 if y
(denominator) is zero.
meridian
.
backend
.
divide_no_nan
(
x
,
y
,
name
=
None
)
For example:
>>>
tf
.
constant
(
3.0
)
/
0.0
< tf
.
Tensor
:
shape
=
(),
dtype
=
float32
,
numpy
=
inf
>
>>>
tf
.
math
.
divide_no_nan
(
3.0
,
0.0
)
< tf
.
Tensor
:
shape
=
(),
dtype
=
float32
,
numpy
=
0.0
>
Note that 0 is returned if y
is 0 even if x
is nonfinite:
>>>
tf
.
math
.
divide_no_nan
(
np
.
nan
,
0.0
)
< tf
.
Tensor
:
shape
=(),
dtype
=
float32
,
numpy
=
0.0
>
A Tensor
of a floating or integer dtype.
A Tensor
with the same dtype as x
and a compatible shape.
A name for the operation (optional).
The element-wise quotient as in tf.math.divide(x, y)
,
except that division by zero produces 0.0
, not nan
.
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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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-16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.divide_no_nan\n\n\u003cbr /\u003e\n\nComputes a safe divide which returns 0 if `y` (denominator) is zero. \n\n meridian.backend.divide_no_nan(\n x, y, name=None\n )\n\n#### For example:\n\n \u003e\u003e\u003e tf.constant(3.0) / 0.0\n \u003ctf.Tensor: shape=(), dtype=float32, numpy=inf\u003e\n \u003e\u003e\u003e tf.math.divide_no_nan(3.0, 0.0)\n \u003ctf.Tensor: shape=(), dtype=float32, numpy=0.0\u003e\n\nNote that 0 is returned if `y` is 0 even if `x` is nonfinite: \n\n \u003e\u003e\u003e tf.math.divide_no_nan(np.nan, 0.0)\n \u003ctf.Tensor: shape=(), dtype=float32, numpy=0.0\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|---------------------------------------------------------------|\n| `x` | A `Tensor` of a floating or integer dtype. |\n| `y` | A `Tensor` with the same dtype as `x` and a compatible shape. |\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| The element-wise quotient as in `tf.math.divide(x, y)`, except that division by zero produces `0.0`, not `nan`. ||\n\n\u003cbr /\u003e"]]
