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.
|