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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.

If x is a SparseTensor, returns SparseTensor(x.indices, tf.math.erf(x.values, ...), x.dense_shape)