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# tf.raw_ops.Erf

Computes the Gauss error function of x element-wise. In statistics, for non-negative values of $$x$$, the error function has the following interpretation: for a random variable $$Y$$ that is normally distributed with mean 0 and variance $$1/\sqrt{2}$$, $$erf(x)$$ is the probability that $$Y$$ falls in the range $$[−x, x]$$.

#### For example:

tf.math.erf([[1.0, 2.0, 3.0], [0.0, -1.0, -2.0]])
<tf.Tensor: shape=(2, 3), dtype=float32, numpy=
array([[ 0.8427007,  0.9953223,  0.999978 ],
[ 0.       , -0.8427007, -0.9953223]], dtype=float32)>

x A Tensor. Must be one of the following types: bfloat16, half, float32, float64.
name A name for the operation (optional).

A Tensor. Has the same type as x.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]