# tf.bitwise.invert

Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010.

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))
``````

`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).

A `Tensor`. Has the same type as `x`.

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