tfp.experimental.distributions.marginal_fns.ps.sqrt

Computes element-wise square root of the input tensor.

x = tf.constant([[4.0], [16.0]])
tf.sqrt(x)
<tf.Tensor: shape=(2, 1), dtype=float32, numpy=
  array([[2.],
         [4.]], dtype=float32)>
y = tf.constant([[-4.0], [16.0]])
tf.sqrt(y)
<tf.Tensor: shape=(2, 1), dtype=float32, numpy=
  array([[nan],
         [ 4.]], dtype=float32)>
z = tf.constant([[-1.0], [16.0]], dtype=tf.complex128)
tf.sqrt(z)
<tf.Tensor: shape=(2, 1), dtype=complex128, numpy=
  array([[0.0+1.j],
         [4.0+0.j]])>

x A tf.Tensor of type bfloat16, half, float32, float64, complex64, complex128
name A name for the operation (optional).

A tf.Tensor of same size, type and sparsity as x.

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