message: Update `tf.math.minimum` documentation.
diff: @@ -7,11 +7,29 @@ op {
  name: "minimum"
  }
  description: <<END
  -Example:
  +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.
  +
  +>>> 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)>
  +
  +If inputs are not tensors, they will be converted to tensors. See
  +`tf.convert_to_tensor`.
  +
  +>>> x = tf.constant([-3.], dtype=tf.float32)
  +>>> tf.math.minimum([-5], x)
  +<tf.Tensor: shape=(1,), dtype=float32, numpy=array([-5.], dtype=float32)>
  +
  END
  }
  