Logical AND function.
tf.math.logical_and(
    x, y, name=None
)
The operation works for the following input types:
- Two single elements of type 
bool 
- One 
tf.Tensor of type bool and one single bool, where the result will
be calculated by applying logical AND with the single element to each
element in the larger Tensor. 
- Two 
tf.Tensor objects of type bool of the same shape. In this case,
the result will be the element-wise logical AND of the two input tensors. 
Usage:
a = tf.constant([True])
b = tf.constant([False])
tf.math.logical_and(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])>
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])>
Args | 
x
 | 
A tf.Tensor type bool.
 | 
y
 | 
A tf.Tensor of type bool.
 | 
name
 | 
A name for the operation (optional).
 | 
Returns | 
A tf.Tensor of type bool with the same size as that of x or y.
 |