tf.compat.v1.math.minimum  |  TensorFlow v2.16.1 (original) (raw)

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

tf.compat.v1.math.minimum(
    x: Annotated[Any, tf.raw_ops.Any],
    y: Annotated[Any, tf.raw_ops.Any],
    name=None
) -> Annotated[Any, tf.raw_ops.Any]

Both inputs are number-type tensors (except complex). minimum expects that both tensors have the same dtype.

Examples:

x = tf.constant([0., 0., 0., 0.]) y = tf.constant([-5., -2., 0., 3.]) tf.math.minimum(x, y) <tf.Tensor: shape=(4,), dtype=float32, numpy=array([-5., -2., 0., 0.], dtype=float32)>

Note that minimum supports broadcast semantics for x and y.

x = tf.constant([-5., 0., 0., 0.]) y = tf.constant([-3.]) tf.math.minimum(x, y) <tf.Tensor: shape=(4,), dtype=float32, numpy=array([-5., -3., -3., -3.], dtype=float32)>

The reduction version of this elementwise operation is tf.math.reduce_min