tf.math.logical_and  |  TensorFlow v2.16.1 (original) (raw)

>>> a = tf.constant([True])
>>> b = tf.constant([False])
>>> tf.math.logical_and(a, b)
<tf.Tensor: shape=(1,), dtype=bool, numpy=array([False])>
>>> a & b
<tf.Tensor: shape=(1,), dtype=bool, numpy=array([False])>

c = tf.constant([True]) x = tf.constant([False, True, True, False]) tf.math.logical_and(c, x) <tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, False])> c & x <tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, False])>

y = tf.constant([False, False, True, True]) z = tf.constant([False, True, False, True]) tf.math.logical_and(y, z) <tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, False, False, True])> y & z <tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, False, False, True])>

This op also supports broadcasting

tf.logical_and([[True, False]], [[True], [False]]) <tf.Tensor: shape=(2, 2), dtype=bool, numpy= array([[ True, False], [False, False]])>