tf.bitwise.invert
Invert (flip) each bit of supported types; for example, type uint8
value 01010101 becomes 10101010.
tf.bitwise.invert( x, name=None )
Flip each bit of supported types. For example, type int8
(decimal 2) binary 00000010 becomes (decimal -3) binary 11111101. This operation is performed on each element of the tensor argument x
.
Example:
import tensorflow as tf from tensorflow.python.ops import bitwise_ops # flip 2 (00000010) to -3 (11111101) tf.assert_equal(-3, bitwise_ops.invert(2)) dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64, dtypes.uint8, dtypes.uint16, dtypes.uint32, dtypes.uint64] inputs = [0, 5, 3, 14] for dtype in dtype_list: # Because of issues with negative numbers, let's test this indirectly. # 1. invert(a) and a = 0 # 2. invert(a) or a = invert(0) input_tensor = tf.constant([0, 5, 3, 14], dtype=dtype) not_a_and_a, not_a_or_a, not_0 = [bitwise_ops.bitwise_and( input_tensor, bitwise_ops.invert(input_tensor)), bitwise_ops.bitwise_or( input_tensor, bitwise_ops.invert(input_tensor)), bitwise_ops.invert( tf.constant(0, dtype=dtype))] expected = tf.constant([0, 0, 0, 0], dtype=tf.float32) tf.assert_equal(tf.cast(not_a_and_a, tf.float32), expected) expected = tf.cast([not_0] * 4, tf.float32) tf.assert_equal(tf.cast(not_a_or_a, tf.float32), expected) # For unsigned dtypes let's also check the result directly. if dtype.is_unsigned: inverted = bitwise_ops.invert(input_tensor) expected = tf.constant([dtype.max - x for x in inputs], dtype=tf.float32) tf.assert_equal(tf.cast(inverted, tf.float32), tf.cast(expected, tf.float32))
Args | |
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x | A Tensor . Must be one of the following types: int8 , int16 , int32 , int64 , uint8 , uint16 , uint32 , uint64 . |
name | A name for the operation (optional). |
Returns | |
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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/r2.4/api_docs/python/tf/bitwise/invert