Returns the max of x and y (i.e. x > y ? x : y) element-wise.
tfp.experimental.distributions.marginal_fns.ps.maximum(
x: Annotated[Any, TV_Maximum_T], y: Annotated[Any, TV_Maximum_T], name=None
) -> Annotated[Any, TV_Maximum_T]
Example:
x = tf.constant([0., 0., 0., 0.])
y = tf.constant([-2., 0., 2., 5.])
tf.math.maximum(x, y)
<tf.Tensor: shape=(4,), dtype=float32, numpy=array([0., 0., 2., 5.], dtype=float32)>
Note that maximum
supports broadcast semantics for x
and y
.
x = tf.constant([-5., 0., 0., 0.])
y = tf.constant([-3.])
tf.math.maximum(x, y)
<tf.Tensor: shape=(4,), dtype=float32, numpy=array([-3., 0., 0., 0.], dtype=float32)>
The reduction version of this elementwise operation is tf.math.reduce_max
Returns | |
---|---|
A Tensor . Has the same type as x .
|