[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976

Merged
Gasoonjia merged 13 commits into
pytorch:mainfrom
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged

[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
pytorch:mainfrom
keyprocedure:add-dim-order-clone-transform

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@keyprocedurekeyprocedure commented Jul 29, 2025•
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Summary

This is PR 3 of 3 implementing a dim order aware clone op.

This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.

Related PRs:

  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone

Fixes#12645

Test plan

Added tests to verify:

  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.

All tests pass via:
python -m unittest exir.tests.test_memory_format_ops_pass
python -m unittest backends.transforms.test.test_remove_clone_ops

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976

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

⏳ 51 Pending, 1 Unrelated Failure

As of commit 15ff154 with merge base 29cec35 (image):

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-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 Jul 29, 2025
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keyprocedure commented Jul 29, 2025

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@pytorchbot label "release notes: none"

@pytorch-botpytorch-botBot added the release notes: none Do not include this in the release notes label Jul 29, 2025
This was referenced Jul 30, 2025
Merged
Merged
Gasoonjia added a commit that referenced this pull request Aug 11, 2025
@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
digantdesai reviewed Aug 14, 2025
View reviewed changes
Comment threadbackends/transforms/remove_clone_ops.py Outdated
if node.op != "call_function":
continue

# Identify clone_dim_order ops with unchanged memory layout.

@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.

@keyprocedurekeyprocedureAug 16, 2025

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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.

agrima1304 pushed a commit to agrima1304/executorch that referenced this pull request Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit that referenced this pull request Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedurekeyprocedure mentioned this pull request Aug 27, 2025
Merged
Gasoonjia added a commit that referenced this pull request Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedure
keyprocedure marked this pull request as ready for review September 4, 2025 20:12
keyprocedure
keyprocedure commented Sep 4, 2025
View reviewed changes
Comment threadbackends/transforms/remove_clone_ops.py Outdated

to_be_remove = n
# Skip removal of clone ops that modify layout/dim order.
if self.aten_clone_is_non_identity(

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UFMT formatter forces this split style

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keyprocedure commented Sep 4, 2025

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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?

Gasoonjia
Gasoonjia reviewed Sep 4, 2025
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Thanks @keyprocedure for your help!

Some subtle feedback but overall look great!

Comment threadbackends/transforms/remove_clone_ops.py Outdated
dead_code_elimination_pass(graph_module)
return PassResult(graph_module, True)

def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:

@GasoonjiaGasoonjiaSep 4, 2025

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Let's combine the two check functions, aten_clone_is_non_identity and _clone_dim_order_is_non_identity into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.

Comment threadexir/tests/test_memory_format_ops_pass.py Outdated
self.assertTrue(is_contiguous_dim_order(actual))
self.assertTrue(is_contiguous_dim_order(expected))

def test_op_clone_replacement_channels_last_survives(self):

@GasoonjiaGasoonjiaSep 4, 2025

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lets move test to test_remove_clone_ops.py

Gasoonjia
Gasoonjia reviewed Sep 5, 2025
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LGTM! Thansk for your wonderful work!
Only a name update suggestion but i think we can stamp it as long as ci passes!

Comment threadbackends/transforms/test/test_remove_clone_ops.py Outdated
transformed_gm.code
)

def test_clone_channels_last_survives(self):

@GasoonjiaGasoonjiaSep 5, 2025

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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor

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Oh right, that makes more sense

@keyprocedure

keyprocedure commented Sep 5, 2025

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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!

No problem!
Should I push the name change now or would you rather we do it in another PR?

@Gasoonjia

Gasoonjia commented Sep 5, 2025

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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!

No problem! Should I push the name change now or would you rather we do it in another PR?

Let's change it in this PR if you have time!

@keyprocedure

keyprocedure commented Sep 5, 2025

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Done :)

@mergennachin

mergennachin commented Sep 5, 2025

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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini

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keyprocedure commented Sep 5, 2025

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@mergennachin good catch, I've added the test file to the pytest config.

@keyprocedure

keyprocedure commented Sep 8, 2025

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Hi @Gasoonjia, the CI failures are unrelated to this PR:

  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5

Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go

@Gasoonjia

Gasoonjia commented Sep 8, 2025

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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.

@Gasoonjia

Gasoonjia commented Sep 8, 2025

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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?
Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.

@keyprocedure

keyprocedure commented Sep 8, 2025•
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.
Thanks for taking care of the internal CI issues!

@Gasoonjia

Gasoonjia commented Sep 9, 2025

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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.

@Gasoonjia
Gasoonjia merged commit dbac09c into pytorch:mainSep 9, 2025
239 of 278 checks passed
@keyprocedure

keyprocedure commented Sep 9, 2025•
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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.

@Gasoonjia

Gasoonjia commented Sep 9, 2025

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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!

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Add dim order variant clone operator

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@keyprocedure@Gasoonjia@mergennachin@digantdesai
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
Merged
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Conversation
@keyprocedure
@keyprocedurekeyprocedure
commented
Jul 29, 2025•

edited

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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
@pytorch-bot
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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Aug 11, 2025
@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
digantdesai
reviewed
Aug 14, 2025
View reviewed changes
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
@keyprocedurekeyprocedureAug 16, 2025

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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
agrima1304 pushed a commit
to agrima1304/executorch
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
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mentioned this pull request
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Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
Outdated

 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
Outdated

 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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try {
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[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
Merged
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
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Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedurekeyprocedure
mentioned this pull request
Aug 27, 2025
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Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
Outdated

 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
Outdated

 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
@Gasoonjia
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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, 'i');
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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");
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
Merged
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
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Aug 14, 2025
View reviewed changes
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
@keyprocedurekeyprocedureAug 16, 2025

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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
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Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedurekeyprocedure
mentioned this pull request
Aug 27, 2025
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Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
@GasoonjiaGasoonjiaSep 4, 2025

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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
Outdated

 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
@GasoonjiaGasoonjiaSep 4, 2025

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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
Outdated

 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
@Gasoonjia
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merged commit dbac09c
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239 of 278 checks passed

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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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, '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";
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Skip to content
[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
Merged
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
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@keyprocedurekeyprocedure
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Jul 29, 2025•

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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
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Aug 14, 2025
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
@keyprocedurekeyprocedureAug 16, 2025

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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
agrima1304 pushed a commit
to agrima1304/executorch
that referenced
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Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedurekeyprocedure
mentioned this pull request
Aug 27, 2025
 Merged

Gasoonjia added a commit
that referenced
this pull request
Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedure
keyprocedure
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September 4, 2025 20:12
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
@GasoonjiaGasoonjiaSep 4, 2025

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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
Outdated

 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
@GasoonjiaGasoonjiaSep 4, 2025

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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
Outdated

 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
@GasoonjiaGasoonjiaSep 5, 2025

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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
@mergennachin
mergennachin
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
@Gasoonjia
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
@Gasoonjia
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
@Gasoonjia
Gasoonjia
merged commit dbac09c
into
pytorch:mainSep 9, 2025

239 of 278 checks passed

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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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@keyprocedure@Gasoonjia@mergennachin@digantdesai

, '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
[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
Merged
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
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@keyprocedure
@keyprocedurekeyprocedure
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Jul 29, 2025•

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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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Gasoonjia added a commit
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Aug 11, 2025
@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
digantdesai
reviewed
Aug 14, 2025
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
@keyprocedurekeyprocedureAug 16, 2025

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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
agrima1304 pushed a commit
to agrima1304/executorch
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedurekeyprocedure
mentioned this pull request
Aug 27, 2025
 Merged

Gasoonjia added a commit
that referenced
this pull request
Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedure
keyprocedure
marked this pull request as ready for review
September 4, 2025 20:12
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Sep 4, 2025
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
Gasoonjia
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
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 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
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 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
@Gasoonjia
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239 of 278 checks passed

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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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, '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");
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} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
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pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
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keyprocedure:add-dim-order-clone-transform
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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
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Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
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this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
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Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
Outdated

 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
Outdated

 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
@Gasoonjia
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merged commit dbac09c
into
pytorch:mainSep 9, 2025

239 of 278 checks passed

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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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[EXIR] Update RemoveCloneOpsTransform to be dim order aware - #12976
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Gasoonjia merged 13 commits into
pytorch:mainfrom 
keyprocedure:add-dim-order-clone-transform
Sep 9, 2025
Merged
[EXIR] Update RemoveCloneOpsTransform to be dim order aware#12976
Gasoonjia merged 13 commits into
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keyprocedure:add-dim-order-clone-transform
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Jul 29, 2025•

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Summary
This is PR 3 of 3 implementing a dim order aware clone op.
This PR updates the clone removal pass to retain layout changing aten.clone and _clone_dim_order ops and remove no-op clones, ensuring layout/dim order is preserved through export.
Related PRs:
  • PR 1: #12974 - Add _clone_dim_order portable kernel
  • PR 2: #13735 - Register _clone_dim_order op and map aten.clone
Fixes#12645
Test plan
Added tests to verify:
  • Clones that change layout are preserved.
  • Clones with unchanged layout (identity ops) are removed.
All tests pass via:

python -m unittest exir.tests.test_memory_format_ops_pass

python -m unittest backends.transforms.test.test_remove_clone_ops
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12976
Note: Links to docs will display an error until the docs builds have been completed.
⏳ 51 Pending, 1 Unrelated Failure
As of commit 15ff154 with merge base 29cec35 (image):
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.
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Aug 11, 2025
@keyprocedure@Gasoonjia
Add _clone_dim_order portable kernel (#12974)
3a02146
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [#12971](#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixes#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
digantdesai
digantdesai
reviewed
Aug 14, 2025
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 if node.op != "call_function":
 continue

 # Identify clone_dim_order ops with unchanged memory layout.
@digantdesaidigantdesaiAug 14, 2025

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if we are supporting aten.clone elimination through this pass then we should similarly check memory_format arg.
@keyprocedurekeyprocedureAug 16, 2025

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Great point! I added the check for aten.clone and updated the tests. I'll refactor/simplify the test cases if needed once we land the AOT PR since it includes its own tests.
agrima1304 pushed a commit
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that referenced
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Aug 26, 2025
@keyprocedure@Gasoonjia@agrima1304
Add _clone_dim_order portable kernel (pytorch#12974)
35db5b7
### Summary
This is PR 1 of 3 implementing a dim order aware clone op. Currently, clone ops are removed during export as no-ops, causing memory
layout (dim order) changes to be lost. This can cause backend failures,
incorrect outputs when ops expect specific layouts, and performance
degradation. This set of PRs introduces a dim order aware clone op,
`_clone_dim_order`, which preserves memory layout changes by explicitly
storing dim order information. This is implemented by replacing standard
clone ops with this variant during export and updating the clone removal
transform to preserve clones that change layout.
This PR adds the portable CPU kernel for the `_clone_dim_order` op,
implementing a clone variant that preserves dim order at runtime. The
portable kernel validates dtype and layout compatibility, resizes the
output tensor if needed, and performs an element wise clone of the
tensors.
Note: A future PR will add the ATen kernel for `_clone_dim_order`.
Related PRs:
- PR 2: [pytorch#12971](pytorch#12971) -
Register `_clone_dim_order` op and map `aten.clone`
- PR 3: [pytorch#12976](pytorch#12976) -
Update RemoveCloneOpsTransform to be dim_order aware
Fixespytorch#12645 ### Test plan
Added kernel runtime tests to verify:
- Tensors of all real dtypes are cloned correctly.
- Failure when input and output tensor shapes mismatch.
- Failure with unsupported memory formats.
- Failure when `non_blocking=true` since the portable kernel only
supports blocking data transfer.
- Dynamic shape outputs are cloned with correct values.
- Layout conversions are cloned correctly for `contiguous` to
`channels_last`, `channels_last` to `contiguous`, and `channels_last` is
preserved.
All runtime tests pass via:
`build-ninja/kernels/test/portable_kernels_test`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Gasoonjia added a commit
that referenced
this pull request
Aug 26, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#12971)
130cafc
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone`
ops to `dim_order_ops._clone_dim_order` in EXIR during export to
preserve memory layout changes (contiguous/channels_last). It also
updates Core ML and ARM backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedurekeyprocedure
mentioned this pull request
Aug 27, 2025
 Merged

Gasoonjia added a commit
that referenced
this pull request
Sep 4, 2025
@keyprocedure@Gasoonjia@digantdesai
[EXIR] Register _clone_dim_order op and map aten.clone (#13735)
c5ff74c
### Summary
This is PR 2 of 3 implementing a dim order aware clone op. This PR registers the new `_clone_dim_order` op and maps `aten.clone` to
`dim_order_ops._clone_dim_order` in EXIR during export to preserve
memory layout changes (contiguous/channels_last). It also updates the
Core ML, ARM, and Qualcomm backends to handle the new clone op.
Related PRs:
- PR 1: [#12974](#12974) - Add
`_clone_dim_order` portable kernel
- PR 3: [#12976](#12976) -
Update RemoveCloneOpsTransform to be dim order aware
Fixes#12645 ### Test plan
- Operator level tests to verify kernel behavior for layout preservation
and changes.
- Graph level checks to confirm that clone mapping occurs.
- End to end tests to validate that functional clone behavior is
unchanged.
- Backend tests to ensure clone semantics are preserved.
All tests pass via:
`python -m unittest exir.tests.test_memory_format_ops_pass`
`python -m unittest backends.apple.coreml.test.test_torch_ops`
`pytest backends/arm/test/ops/test_clone.py`
`pytest backends/arm/test/passes/test_remove_clone_pass.py`
---------
Co-authored-by: Gasoonjia <gasoonjia@meta.com>
Co-authored-by: Digant Desai <digantdesai@meta.com>
@keyprocedure
keyprocedure
marked this pull request as ready for review
September 4, 2025 20:12
keyprocedure
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Sep 4, 2025
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Comment threadbackends/transforms/remove_clone_ops.py
Outdated


 to_be_remove = n
 # Skip removal of clone ops that modify layout/dim order.
 if self.aten_clone_is_non_identity(
@keyprocedurekeyprocedureSep 4, 2025

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UFMT formatter forces this split style
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@Gasoonjia this PR is ready to go, would you mind reviewing when you get a chance?
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Thanks @keyprocedure for your help!
Some subtle feedback but overall look great!
Comment threadbackends/transforms/remove_clone_ops.py
Outdated

 dead_code_elimination_pass(graph_module)
 return PassResult(graph_module, True)

 def aten_clone_is_non_identity(self, node: torch.fx.Node) -> bool:
@GasoonjiaGasoonjiaSep 4, 2025

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Let's combine the two check functions, aten_clone_is_non_identity  and _clone_dim_order_is_non_identity  into a single function (maybe called _is_non_identity_clone). Under current scenario we will always use the funcs together and this func should be private.
Comment threadexir/tests/test_memory_format_ops_pass.py
Outdated

 self.assertTrue(is_contiguous_dim_order(actual))
 self.assertTrue(is_contiguous_dim_order(expected))

 def test_op_clone_replacement_channels_last_survives(self):
@GasoonjiaGasoonjiaSep 4, 2025

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lets move test to test_remove_clone_ops.py
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LGTM! Thansk for your wonderful work!

Only a name update suggestion but i think we can stamp it as long as ci passes!
Comment threadbackends/transforms/test/test_remove_clone_ops.py
Outdated

 transformed_gm.code
 )

 def test_clone_channels_last_survives(self):
@GasoonjiaGasoonjiaSep 5, 2025

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maybe should called it test_clone_non_identity_survives? cuz it survives because of mutating memory_format / dim_order, rather than cloning a channels_last tensor
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Oh right, that makes more sense
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem!

Should I push the name change now or would you rather we do it in another PR?
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LGTM! Thansk for your wonderful work! Only a name update suggestion but i think we can stamp it as long as ci passes!
No problem! Should I push the name change now or would you rather we do it in another PR?
Let's change it in this PR if you have time!
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Done :)
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@keyprocedure we might have to add the tests here: https://github.com/pytorch/executorch/blob/main/pytest.ini
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@mergennachin good catch, I've added the test file to the pytest config.
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Hi @Gasoonjia, the CI failures are unrelated to this PR:
  • Documentation upload error
  • NXP backend: Missing out variants: {'quantized_decomposed::quantize_per_tensor', 'quantized_decomposed::dequantize_per_tensor'}
  • Config: Error merging override base.model_class=qwen2_5
Feel free to let me know if you'd like anything in this PR changed, otherwise this should be good to go
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Thanks for your help @keyprocedure ! I think nxp issue should be solved already. Let me rebase and retest.
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Hi @keyprocedure ci looks good but there's a conflict in pytest.ini. Mind take a look?

Also #13735 raised some issue in our internal ci and i have a fix here #14088. I will land this PR after the fix PR land.
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@Gasoonjia, the merge conflict is resolved: backend/transforms had been added to the pytest config, so I removed the explicit backends/transforms/test/test_remove_clone_ops.py path.

Thanks for taking care of the internal CI issues!
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#14088 has been landed but this ci raised some issue. Looks like it is preexisted in our codebase. Will rebase and retrigger ci.
@Gasoonjia
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merged commit dbac09c
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pytorch:mainSep 9, 2025

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I appreciate your reviews across all the PRs @Gasoonjia, and for handling CI and merges.
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@keyprocedure thank you for such active contribution! Looking forward to work with you in the future!
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Add dim order variant clone operator


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