Xor#

  • Domain: ai.onnx

  • Since version: 7

Returns the tensor resulted from performing the Xor logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

Inputs

  • A (T): First input operand for the logical operator.

  • B (T): Second input operand for the logical operator.

Outputs

  • C (T1): Result tensor.

Type Constraints

  • T: Constrain input to boolean tensor. Allowed types: tensor(bool).

  • T1: Constrain output to boolean tensor. Allowed types: tensor(bool).

Examples#

test_cc_xor

Inputs:
  x: shape=(2, 2), dtype=bool
    [[ True, False],
     [ True, False]]
  y: shape=(2, 2), dtype=bool
    [[ True,  True],
     [False, False]]

Outputs:
  z: shape=(2, 2), dtype=bool
    [[False,  True],
     [ True, False]]

test_cc_xor_bcast

Inputs:
  x: shape=(2, 2), dtype=bool
    [[ True, False],
     [ True, False]]
  y: shape=(), dtype=bool
    True

Outputs:
  z: shape=(2, 2), dtype=bool
    [[False,  True],
     [False,  True]]

Differences with previous version (1)#

SchemaDiff: Xor (domain 'ai.onnx')

  • old version: 1

  • new version: 7

  • breaking: no

Documentation:

  • line similarity: 0.40 (+1/-5 lines)

--- Xor v1
+++ Xor v7
@@ -1,7 +1,3 @@

 Returns the tensor resulted from performing the `Xor` logical operation
-elementwise on the input tensors `A` and `B`.
-
-If broadcasting is enabled, the right-hand-side argument will be broadcasted
-to match the shape of left-hand-side argument. See the doc of `Add` for a
-detailed description of the broadcasting rules.
+elementwise on the input tensors `A` and `B` (with Numpy-style broadcasting support).

Version History#