MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

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❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

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@meta-clameta-claBot 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 22, 2026
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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

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Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

AlessandroVacca commented Apr 23, 2026

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

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{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Good First Issue: Add Full Integer Support for aten.bitwise_not

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Skip to content

MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
@pytorch-bot

pytorch-botBot commented Apr 22, 2026

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

❗ 1 Active SEVs

There are 1 currently active SEVs. If your PR is affected, please view them below:

❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

As of commit bbe7c56 with merge base 56da964 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

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

@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

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Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

@nil-is-all

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
@claude

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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

@metascroy

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

AlessandroVacca commented Apr 23, 2026

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Labels

CLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: mlxIssues related to MLX Backend: Metal-accelerated inference on Apple Siliconrelease notes: appleChanges to the Apple backend delegate

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Successfully merging this pull request may close these issues.

Good First Issue: Add Full Integer Support for aten.bitwise_not

4 participants

@AlessandroVacca@nil-is-all@metascroy
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

❗ 1 Active SEVs

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❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

As of commit bbe7c56 with merge base 56da964 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

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@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

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Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

@nil-is-all

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Good First Issue: Add Full Integer Support for aten.bitwise_not

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@AlessandroVacca@nil-is-all@metascroy
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
@pytorch-bot

pytorch-botBot commented Apr 22, 2026

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

❗ 1 Active SEVs

There are 1 currently active SEVs. If your PR is affected, please view them below:

❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

As of commit bbe7c56 with merge base 56da964 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

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

@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

@nil-is-all

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
@claude

claudeBot commented Apr 23, 2026

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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

@metascroy

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

AlessandroVacca commented Apr 23, 2026

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Labels

CLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: mlxIssues related to MLX Backend: Metal-accelerated inference on Apple Siliconrelease notes: appleChanges to the Apple backend delegate

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Development

Successfully merging this pull request may close these issues.

Good First Issue: Add Full Integer Support for aten.bitwise_not

4 participants

@AlessandroVacca@nil-is-all@metascroy
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

Conversation

@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
@pytorch-bot

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

❗ 1 Active SEVs

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❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

As of commit bbe7c56 with merge base 56da964 (image):

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@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

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Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Labels

CLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: mlxIssues related to MLX Backend: Metal-accelerated inference on Apple Siliconrelease notes: appleChanges to the Apple backend delegate

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Good First Issue: Add Full Integer Support for aten.bitwise_not

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@AlessandroVacca@nil-is-all@metascroy
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
@pytorch-bot

pytorch-botBot commented Apr 22, 2026

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

❗ 1 Active SEVs

There are 1 currently active SEVs. If your PR is affected, please view them below:

❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

As of commit bbe7c56 with merge base 56da964 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

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

@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

@nil-is-all

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
@claude

claudeBot commented Apr 23, 2026

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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

@metascroy

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

AlessandroVacca commented Apr 23, 2026

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Labels

CLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: mlxIssues related to MLX Backend: Metal-accelerated inference on Apple Siliconrelease notes: appleChanges to the Apple backend delegate

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Development

Successfully merging this pull request may close these issues.

Good First Issue: Add Full Integer Support for aten.bitwise_not

4 participants

@AlessandroVacca@nil-is-all@metascroy
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

MLX delegate: add integer support for aten.bitwise_not - #19053

Merged
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
@pytorch-bot

pytorch-botBot commented Apr 22, 2026

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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

❗ 1 Active SEVs

There are 1 currently active SEVs. If your PR is affected, please view them below:

❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

As of commit bbe7c56 with merge base 56da964 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

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

@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

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Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

@nil-is-all

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

AlessandroVacca commented Apr 23, 2026

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Good First Issue: Add Full Integer Support for aten.bitwise_not

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@AlessandroVacca@nil-is-all@metascroy
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MLX delegate: add integer support for aten.bitwise_not - #19053

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metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int
Apr 25, 2026
Merged

MLX delegate: add integer support for aten.bitwise_not#19053
metascroy merged 5 commits into
pytorch:mainfrom
AlessandroVacca:mlx-bitwise-not-int

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@AlessandroVacca

@AlessandroVaccaAlessandroVacca commented Apr 22, 2026

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Summary

Fixes#18924
Extends aten.bitwise_not support in the MLX delegate to handle integer tensors, not just boolean tensors.
Previously the handler only dispatched to LogicalNotNode for bool and raised NotImplementedError for all other dtypes. This adds a dedicated BitwiseInvertNode backed by mlx::core::bitwise_invert, and updates the handler to dispatch based on dtype:

  • boolLogicalNotNode (unchanged)
  • int32, int64BitwiseInvertNode

Changes:

  • serialization/schema.fbs: add BitwiseInvertNode table and append to OpNode union
  • runtime/MLXInterpreter.h: add exec_bitwise_invert() and dispatch case
  • ops.py: update _bitwise_not_handler to dispatch to BitwiseInvertNode for integers
  • test/test_ops.py: add bitwise_not_int test for int32 and int64

Test plan

All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.

  • python3 -m py_compile backends/mlx/ops.py backends/mlx/test/test_ops.py
  • python3 backends/mlx/serialization/generate.py
  • python3 -m executorch.backends.mlx.test.run_all_tests bitwise_not_int

Test output

============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================

cc @metascroy

CopilotAI review requested due to automatic review settings April 22, 2026 20:59
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pytorch-botBot commented Apr 22, 2026

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19053

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❌ 14 New Failures, 15 Pending, 5 Unrelated Failures

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@meta-clameta-claBot 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 22, 2026
@AlessandroVacca

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@pytorchbot label "release notes: apple"

@pytorch-botpytorch-botBot added the release notes: apple Changes to the Apple backend delegate label Apr 22, 2026

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not to support integer tensors by introducing a new BitwiseInvertNode backed by MLX bitwise_invert, while keeping the existing boolean lowering via LogicalNotNode.

Changes:

  • Add BitwiseInvertNode to the FlatBuffers schema and OpNode union.
  • Add MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Update the Python op handler to emit BitwiseInvertNode for non-bool inputs and add a basic integer test case.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

FileDescription
backends/mlx/serialization/schema.fbsAdds BitwiseInvertNode table and appends it to the OpNode union for serialization.
backends/mlx/runtime/MLXInterpreter.hImplements exec_bitwise_invert() and adds interpreter dispatch for OpCode::BITWISE_INVERT.
backends/mlx/ops.pyUpdates aten.bitwise_not handler to emit BitwiseInvertNode for non-bool inputs.
backends/mlx/test/test_ops.pyAdds a unary op test for integer torch.bitwise_not.

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Comment threadbackends/mlx/ops.py
{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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I consciously decided to test only what was asked to be added, lmk if you need also the bool test case

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Test whatever dtypes you assert as supported in the handler.

Also, can you paste the outcome of successful test in the PR description?

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is the test summary in the description of the PR any good?

@nil-is-all

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@claude review this PR

@nil-is-allnil-is-all added the module: mlx Issues related to MLX Backend: Metal-accelerated inference on Apple Silicon label Apr 23, 2026
@claude

claudeBot commented Apr 23, 2026

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Claude encountered an error —— View job

Command failed: git fetch origin --depth=20 pull/19053/head:mlx-bitwise-not-int-c777d55e

I'll analyze this and get back to you.

@metascroy

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Overall looks great @AlessandroVacca! Just a few feedbacks, and then we can merge :)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
CopilotAI review requested due to automatic review settings April 23, 2026 16:26
Removed support for int8, int16, and uint8 data types.
@AlessandroVacca

AlessandroVacca commented Apr 23, 2026

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Should be good now! @metascroy

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Pull request overview

Extends the MLX delegate’s lowering for aten.bitwise_not beyond bool tensors by introducing a dedicated BitwiseInvertNode (backed by MLX bitwise_invert) and dispatching to it for supported integer dtypes.

Changes:

  • Added BitwiseInvertNode to the MLX FlatBuffers schema and appended it to the OpNode union.
  • Added MLX runtime execution support (exec_bitwise_invert) and interpreter dispatch for the new opcode.
  • Updated the Python lowering handler to dispatch: bool -> LogicalNotNode, supported integers -> BitwiseInvertNode, otherwise fallback.
  • Added a unary op test entry for integer torch.bitwise_not (currently int32/int64).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

FileDescription
backends/mlx/serialization/schema.fbsDefines BitwiseInvertNode and appends it to the OpNode union for serialization/runtime compatibility.
backends/mlx/runtime/MLXInterpreter.hImplements and dispatches execution for the new bitwise invert op in the MLX interpreter.
backends/mlx/ops.pyUpdates aten.bitwise_not lowering to route bool to logical-not and integers to bitwise-invert.
backends/mlx/test/test_ops.pyAdds a new unary op test case for integer bitwise_not.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

{"op_name": "abs", "op_fn": torch.abs},
{"op_name": "neg", "op_fn": torch.neg},
{"op_name": "logical_not","op_fn": torch.logical_not, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn": _bool_input_fn()},
{"op_name": "bitwise_not_int", "op_fn": torch.bitwise_not, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn": _int_input_fn()},

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Not advertised anymore whatsoever

CopilotAI review requested due to automatic review settings April 24, 2026 22:30

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Copilot was unable to review this pull request because the user who requested the review is ineligible. To be eligible to request a review, you need a paid Copilot license, or your organization must enable Copilot code review.

@metascroy
metascroy merged commit 0a43e2f into pytorch:mainApr 25, 2026
170 of 192 checks passed
zeel2104 pushed a commit to zeel2104/executorch that referenced this pull request May 5, 2026
### Summary
Fixespytorch#18924
Extends `aten.bitwise_not` support in the MLX delegate to handle integer
tensors, not just boolean tensors.
Previously the handler only dispatched to `LogicalNotNode` for `bool`
and raised `NotImplementedError` for all other dtypes. This adds a
dedicated `BitwiseInvertNode` backed by `mlx::core::bitwise_invert`, and
updates the handler to dispatch based on dtype:
- `bool` → `LogicalNotNode` (unchanged)
- `int32`, `int64` → `BitwiseInvertNode`
#### Changes:
- `serialization/schema.fbs`: add `BitwiseInvertNode` table and append
to `OpNode` union
- `runtime/MLXInterpreter.h`: add `exec_bitwise_invert()` and dispatch
case
- `ops.py`: update `_bitwise_not_handler` to dispatch to
`BitwiseInvertNode` for integers
- `test/test_ops.py`: add `bitwise_not_int` test for `int32` and `int64`
### Test plan
All tests were ran on a machine with an Apple M1 Pro CPU, macOS 26.4.1.
- `python3 -m py_compile backends/mlx/ops.py
backends/mlx/test/test_ops.py`
- `python3 backends/mlx/serialization/generate.py`
- `python3 -m executorch.backends.mlx.test.run_all_tests
bitwise_not_int`
### Test output
```
============================================================
TEST SUMMARY
============================================================
Passed: 6
Failed: 0
============================================================
```
cc @metascroy
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Scott Roy <161522778+metascroy@users.noreply.github.com>
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Labels

CLA SignedThis label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.module: mlxIssues related to MLX Backend: Metal-accelerated inference on Apple Siliconrelease notes: appleChanges to the Apple backend delegate

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Successfully merging this pull request may close these issues.

Good First Issue: Add Full Integer Support for aten.bitwise_not

4 participants

@AlessandroVacca@nil-is-all@metascroy