tf.math.maximum

Returns the max of x and y (i.e. x > y ? x : y) element-wise.

View aliases

Main aliases

tf.maximum

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.maximum

tf.math.maximum(
    x: Annotated[Any, tf.raw_ops.Any],
    y: Annotated[Any, tf.raw_ops.Any],
    name=None
) -> Annotated[Any, tf.raw_ops.Any]

Used in the notebooks

Used in the guide	Used in the tutorials
Extension types Introduction to graphs and tf.function	Generate music with an RNN Instance Segmentation with Model Garden Graph regularization for sentiment classification using synthesized graphs Substantial Undocumented Infection Facilitates the Rapid Dissemination of Novel Coronavirus (SARS-CoV2) Human Pose Classification with MoveNet and TensorFlow Lite

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

Args
x	A Tensor. Must be one of the following types: bfloat16, half, float32, float64, int8, uint8, int16, uint16, int32, uint32, int64, uint64.
y	A Tensor. Must have the same type as x.
name	A name for the operation (optional).

Returns
A Tensor. Has the same type as x.