Elementwise computes the bitwise right-shift of x
and y
.
tf.bitwise.right_shift( x, y, name=None )
Performs a logical shift for unsigned integer types, and an arithmetic shift for signed integer types.
If y
is negative, or greater than or equal to than the width of x
in bits the result is implementation defined.
import tensorflow as tf from tensorflow.python.ops import bitwise_ops import numpy as np dtype_list = [tf.int8, tf.int16, tf.int32, tf.int64] for dtype in dtype_list: lhs = tf.constant([-1, -5, -3, -14], dtype=dtype) rhs = tf.constant([5, 0, 7, 11], dtype=dtype) right_shift_result = bitwise_ops.right_shift(lhs, rhs) print(right_shift_result) # This will print: # tf.Tensor([-1 -5 -1 -1], shape=(4,), dtype=int8) # tf.Tensor([-1 -5 -1 -1], shape=(4,), dtype=int16) # tf.Tensor([-1 -5 -1 -1], shape=(4,), dtype=int32) # tf.Tensor([-1 -5 -1 -1], shape=(4,), dtype=int64) lhs = np.array([-2, 64, 101, 32], dtype=np.int8) rhs = np.array([-1, -5, -3, -14], dtype=np.int8) bitwise_ops.right_shift(lhs, rhs) # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)>
Args | |
---|---|
x | A Tensor . Must be one of the following types: int8 , int16 , int32 , int64 , uint8 , uint16 , uint32 , uint64 . |
y | A Tensor . Must have the same type as x . |
name | A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as x . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/bitwise/right_shift