Returns the truth value of x AND y element-wise.
tf.math.logical_and(
    x, y, name=None
)
  Logical AND function.
Requires that x and y have the same shape or have broadcast-compatible shapes. For example, x and y can be:
bool.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.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.You can also use the & operator instead.
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]])>
 The reduction version of this elementwise operation is tf.math.reduce_all.
| Args | |
|---|---|
| x | A tf.Tensorof type bool. | 
| y | A tf.Tensorof type bool. | 
| name | A name for the operation (optional). | 
| Returns | |
|---|---|
| A tf.Tensorof type bool with the shape thatxandybroadcast to. | 
| Args | |
|---|---|
| x | A Tensorof typebool. | 
| y | A Tensorof typebool. | 
| name | A name for the operation (optional). | 
| Returns | |
|---|---|
| A Tensorof typebool. | 
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/math/logical_and