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Add MLX op handler for aten.bitwise_xor#18983

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Jah-yee:roomwithoutroof/add-mlx-bitwise-xor
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Add MLX op handler for aten.bitwise_xor#18983
Jah-yee wants to merge 1 commit intopytorch:mainfrom
Jah-yee:roomwithoutroof/add-mlx-bitwise-xor

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@Jah-yee Jah-yee commented Apr 18, 2026

Good day

This PR adds support for aten.bitwise_xor in the MLX delegate backend, addressing issue #18927.

Summary

Add BitwiseXorNode to the MLX delegate serialization schema and implement the corresponding handler to enable element-wise bitwise XOR operations on boolean and integer tensors via MLX's native bitwise_xor function.

Changes

  1. schema.fbs: Added BitwiseXorNode table with a, b, and out fields, and registered it in the OpNode union
  2. MLXInterpreter.h: Added exec_bitwise_xor runtime function and corresponding case handler (BITWISE_XOR)
  3. ops.py: Added aten.bitwise_xor to the _BINARY_OPS table-driven handler registry
  4. test_ops.py: Added bitwise_xor_bool and bitwise_xor_int tests using the existing _BINARY_OP_TESTS infrastructure

Testing

Tests can be run with:

python -m executorch.backends.mlx.test.run_all_tests -k bitwise_xor

References

  • MLX C++: array bitwise_xor(const array \&a, const array \&b, StreamOrDevice s = {})
  • PyTorch signature: bitwise_xor(Tensor self, Tensor other) -> Tensor
  • Supported dtypes: int8, int16, int32, int64, uint8, bool

Thank you for your attention. If there are any issues or suggestions, please leave a comment and I will address them promptly.

Warmly,
RoomWithOutRoof

cc @metascroy

Add BitwiseXorNode to the MLX delegate schema and implement the handler
for aten.bitwise_xor, enabling element-wise bitwise XOR operations on
boolean and integer tensors via MLX's native bitwise_xor function.

Changes:
- Add BitwiseXorNode table to schema.fbs
- Register BitwiseXorNode in the OpNode union
- Add exec_bitwise_xor runtime function in MLXInterpreter.h
- Add BITWISE_XOR case handler in the interpreter switch
- Add aten.bitwise_xor handler to _BINARY_OPS in ops.py
- Add bitwise_xor_bool and bitwise_xor_int tests

Fixes: pytorch#18927
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pytorch-bot Bot commented Apr 18, 2026

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/18983

Note: Links to docs will display an error until the docs builds have been completed.

❌ 20 New Failures, 1 Cancelled Job, 1 Unrelated Failure

As of commit 1619c69 with merge base 9ca0ff1 (image):

NEW FAILURES - The following jobs have failed:

CANCELLED JOB - The following job was cancelled. Please retry:

BROKEN TRUNK - The following job failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

This comment was automatically generated by Dr. CI and updates every 15 minutes.

@meta-cla meta-cla Bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Apr 18, 2026
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This PR needs a release notes: label

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@nil-is-all nil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 20, 2026
@nil-is-all nil-is-all requested a review from metascroy April 20, 2026 18:52
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@claude review

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claude Bot commented Apr 20, 2026

Claude finished @nil-is-all's task in 3m 27s —— View job


Code Review: Add MLX op handler for aten.bitwise_xor

  • Gather context: read PR diff and changed files
  • Review schema changes (schema.fbs)
  • Review runtime changes (MLXInterpreter.h)
  • Review Python op handler (ops.py)
  • Review tests (test_ops.py)
  • Review generated files
  • Post review feedback

Critical Issue: Generated files should not be committed

6 of the 10 changed files are auto-generated and have never been tracked in this repository before. They were created by running python backends/mlx/serialization/generate.py and should not be included in this PR:

File Lines Status
backends/mlx/_generated_inspector.py +929 Should not be committed
backends/mlx/runtime/MLXLoader.cpp +2375 Should not be committed
backends/mlx/runtime/MLXLoader.h +1747 Should not be committed
backends/mlx/serialization/_generated/__init__.py +147 Should not be committed
backends/mlx/serialization/_generated_serializers.py +2854 Should not be committed
backends/mlx/serialization/mlx_graph_schema.py +1335 Should not be committed

These files are outputs of generate.py (see backends/mlx/serialization/generate.py:10-26) and have never existed in the repo history until this commit. The templates (MLXLoader.h.tmpl, MLXLoader.cpp.tmpl) are tracked; the generated output is not.

Please remove these 6 files from the PR and ensure only the 4 hand-written changes remain. Fix this →


Bug: Missing import of BitwiseXorNode in ops.py

BitwiseXorNode is used at backends/mlx/ops.py:495 but is not imported in the import block at lines 32-153. This will cause a NameError at runtime when the handler is invoked.

Add BitwiseXorNode to the import from executorch.backends.mlx.serialization.mlx_graph_schema (alphabetically, after Atan2Node). Fix this →


Review of Hand-Written Changes

backends/mlx/serialization/schema.fbs — Looks correct.

  • BitwiseXorNode table with a, b, out fields matches the pattern of other binary ops (LogicalOrNode, Atan2Node, etc.)
  • Placed in the "Math ops - Binary element-wise" section, which is appropriate
  • Appended to the end of the OpNode union, respecting the "append only" comment for backward compatibility

backends/mlx/runtime/MLXInterpreter.h — Looks correct.

  • exec_bitwise_xor at line 1398-1402 follows the exact pattern of adjacent handlers (exec_logical_and, exec_logical_or)
  • Switch case at line 2043-2045 is correctly wired
  • Placement after LOGICAL_OR and before TRI in the switch statement is consistent

backends/mlx/ops.py — Correct pattern, but missing import (see above).

  • Registration in _BINARY_OPS at line 493-498 correctly handles both Tensor and Scalar overloads
  • lift_b=True is correct (allows scalar second operand to be lifted to a tensor)

backends/mlx/test/test_ops.py — Looks good.

  • Two test entries at lines 4209-4210: bitwise_xor_bool and bitwise_xor_int
  • Bool test uses _bool_input_fn() — correct
  • Int test uses int32/int64 with _int_input_fn(0, 256) — good range for bitwise ops
  • Additional integer dtypes (int8, int16, uint8) mentioned in the PR description are not tested, but this is acceptable since they follow the same code path

Summary

Two issues to address before merge:

  1. Remove the 6 generated files — they account for ~9,400 of the ~9,413 added lines and have never been tracked in the repo
  2. Add the missing BitwiseXorNode import in ops.py — without this, the op will fail at runtime

The actual implementation logic (the ~26 hand-written lines across 4 files) is clean and follows the existing patterns correctly.

@metascroy
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Hi @Jah-yee! Thanks for the PR. Similar comments on bitwise_xor PR (make sure you remove the auto-generated files).

@Jah-yee
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Jah-yee commented Apr 22, 2026

Good day @metascroy,

Thank you for the review and for pointing out the issue with auto-generated files.

I have removed the following auto-generated files from the PR:

  • backends/mlx/_generated_inspector.py
  • backends/mlx/runtime/MLXLoader.cpp
  • backends/mlx/runtime/MLXLoader.h
  • backends/mlx/serialization/_generated/init.py
  • backends/mlx/serialization/_generated_serializers.py
  • backends/mlx/serialization/mlx_graph_schema.py

These files are generated by python backends/mlx/serialization/generate.py and should not be committed directly. The remaining files in this PR (schema.fbs, ops.py, MLXInterpreter.h, test_ops.py) are the source files that require manual changes.

Note: I am not the author of this PR (@RoomWithOutRoof is), but I am addressing the review comments as requested.

Thank you for your attention. If there are any issues or suggestions, please leave a comment and I will address them promptly.

Warmly, Jah-yee

@metascroy
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Good day @metascroy,

Thank you for the review and for pointing out the issue with auto-generated files.

I have removed the following auto-generated files from the PR:

  • backends/mlx/_generated_inspector.py
  • backends/mlx/runtime/MLXLoader.cpp
  • backends/mlx/runtime/MLXLoader.h
  • backends/mlx/serialization/_generated/init.py
  • backends/mlx/serialization/_generated_serializers.py
  • backends/mlx/serialization/mlx_graph_schema.py

These files are generated by python backends/mlx/serialization/generate.py and should not be committed directly. The remaining files in this PR (schema.fbs, ops.py, MLXInterpreter.h, test_ops.py) are the source files that require manual changes.

Note: I am not the author of this PR (@RoomWithOutRoof is), but I am addressing the review comments as requested.

Thank you for your attention. If there are any issues or suggestions, please leave a comment and I will address them promptly.

Warmly, Jah-yee

I still see the generated files in the PR?

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@metascroy metascroy left a comment

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Remove generated files from PR.

Maybe also add them to gitignore?

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