TensorFlow 1 version
|
Returns the truth value of x OR y element-wise.
tf.math.logical_or(
x, y, name=None
)
Logical OR function.
Requires that x and y have the same shape or have
broadcast-compatible
shapes. For example, x and y can be:
- Two single elements of type
bool. - One
tf.Tensorof typebooland one singlebool, where the result will be calculated by applying logical OR with the single element to each element in the larger Tensor. - Two
tf.Tensorobjects of typeboolof the same shape. In this case, the result will be the element-wise logical OR of the two input tensors.
You can also use the | operator instead.
Usage:
a = tf.constant([True])b = tf.constant([False])tf.math.logical_or(a, b)<tf.Tensor: shape=(1,), dtype=bool, numpy=array([ True])>a | b<tf.Tensor: shape=(1,), dtype=bool, numpy=array([ True])>
c = tf.constant([False])x = tf.constant([False, True, True, False])tf.math.logical_or(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_or(y, z)<tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, True])>y | z<tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, True])>
This op also supports broadcasting
tf.logical_or([[True, False]], [[True], [False]])<tf.Tensor: shape=(2, 2), dtype=bool, numpy=array([[ True, True],[ True, False]])>
The reduction version of this elementwise operation is tf.math.reduce_any.
Args | |
|---|---|
x
|
A tf.Tensor of 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 shape that x and y broadcast to.
|
Args | |
|---|---|
x
|
A Tensor of type bool.
|
y
|
A Tensor of type bool.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
A Tensor of type bool.
|
TensorFlow 1 version