Elementwise computes the bitwise OR of `x` and `y`.
The result will have those bits set, that are set in `x`, `y` or both. The computation is performed on the underlying representations of `x` and `y`.
For example:
import tensorflow as tf
 from tensorflow.python.ops import bitwise_ops
 dtype_list = [tf.int8, tf.int16, tf.int32, tf.int64,
               tf.uint8, tf.uint16, tf.uint32, tf.uint64]
 
 for dtype in dtype_list:
   lhs = tf.constant([0, 5, 3, 14], dtype=dtype)
   rhs = tf.constant([5, 0, 7, 11], dtype=dtype)
   exp = tf.constant([5, 5, 7, 15], dtype=tf.float32)
 
   res = bitwise_ops.bitwise_or(lhs, rhs)
   tf.assert_equal(tf.cast(res,  tf.float32), exp)  # TRUE
 Constants
| String | OP_NAME | The name of this op, as known by TensorFlow core engine | 
Public Methods
| Output <T> | 
           
            
             asOutput
            
           
           ()
            
            Returns the symbolic handle of the tensor.
            | 
| static <T extends TNumber > BitwiseOr <T> | |
| Output <T> | 
           
            
             z
            
           
           ()
           | 
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public Output <T> asOutput ()
Returns the symbolic handle of the tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static BitwiseOr <T> create ( Scope scope, Operand <T> x, Operand <T> y)
Factory method to create a class wrapping a new BitwiseOr operation.
Parameters
| scope | current scope | 
|---|
Returns
- a new instance of BitwiseOr