tf.raw_ops.BitwiseOr
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Elementwise computes the bitwise OR of x and y.
tf.raw_ops.BitwiseOr(
x, y, name=None
)
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
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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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.BitwiseOr\n\n\u003cbr /\u003e\n\nElementwise computes the bitwise OR of `x` and `y`.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.BitwiseOr`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/BitwiseOr)\n\n\u003cbr /\u003e\n\n tf.raw_ops.BitwiseOr(\n x, y, name=None\n )\n\nThe result will have those bits set, that are set in `x`, `y` or both. The\ncomputation is performed on the underlying representations of `x` and `y`.\n\n#### For example:\n\n import tensorflow as tf\n from tensorflow.python.ops import bitwise_ops\n dtype_list = [tf.int8, tf.int16, tf.int32, tf.int64,\n tf.uint8, tf.uint16, tf.uint32, tf.uint64]\n\n for dtype in dtype_list:\n lhs = tf.constant([0, 5, 3, 14], dtype=dtype)\n rhs = tf.constant([5, 0, 7, 11], dtype=dtype)\n exp = tf.constant([5, 5, 7, 15], dtype=tf.float32)\n\n res = bitwise_ops.bitwise_or(lhs, rhs)\n tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|---------------------------------------------------------------------------------------------------------------------------|\n| `x` | A `Tensor`. Must be one of the following types: `int8`, `int16`, `int32`, `int64`, `uint8`, `uint16`, `uint32`, `uint64`. |\n| `y` | A `Tensor`. Must have the same type as `x`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `x`. ||\n\n\u003cbr /\u003e"]]
