Bump PyTorch pin to 2025-03-25 - #9578

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Bump PyTorch pin to 2025-03-25#9578
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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

⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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resnapshotted the ARM test. we'll see if it builds.

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pinged @digantdesai for advice on how to proceed with ARM failures

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

@zingo

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

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swolchok merged commit 9eea1f1 into mainApr 4, 2025
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swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
@swolchok@kirklandsign
Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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Bump PyTorch pin to 2025-03-25 - #9578

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swolchok merged 16 commits into
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gh/swolchok/394/head
Apr 4, 2025
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Bump PyTorch pin to 2025-03-25#9578
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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

⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

@swolchok
Update
aafeb54
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Update
9f49022
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Update
89c4760
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dd30cfa
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2c5ee5f
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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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0bc272e
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resnapshotted the ARM test. we'll see if it builds.

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bbf612c
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pinged @digantdesai for advice on how to proceed with ARM failures

@zingo

zingo commented Apr 1, 2025

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

@zingo

zingo commented Apr 2, 2025

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@swolchok
Update
f78320d
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@swolchok

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

@swolchok
rebase
a37193c
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@zingo

zingo commented Apr 3, 2025•
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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

@zingo

zingo commented Apr 4, 2025

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

@swolchok
swolchok merged commit 9eea1f1 into mainApr 4, 2025
@swolchok
swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
@swolchok@kirklandsign
Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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Bump PyTorch pin to 2025-03-25 - #9578

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swolchok merged 16 commits into
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Bump PyTorch pin to 2025-03-25#9578
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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

⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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This was referenced Mar 25, 2025
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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

@mergennachin

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

@swolchok
Update
aafeb54
[ghstack-poisoned]
@swolchok
Update
9f49022
[ghstack-poisoned]
@swolchok
Update
89c4760
[ghstack-poisoned]
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Update
dd30cfa
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Update
2c5ee5f
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Update
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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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0bc272e
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resnapshotted the ARM test. we'll see if it builds.

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bbf612c
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pinged @digantdesai for advice on how to proceed with ARM failures

@zingo

zingo commented Apr 1, 2025

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

@zingo

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@swolchok
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f78320d
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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

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rebase
a37193c
[ghstack-poisoned]
@zingo

zingo commented Apr 3, 2025•
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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

@zingo

zingo commented Apr 4, 2025

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

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swolchok merged commit 9eea1f1 into mainApr 4, 2025
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swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
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Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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Bump PyTorch pin to 2025-03-25 - #9578

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Bump PyTorch pin to 2025-03-25#9578
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⏳ 1 Pending, 1 Unrelated Failure

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UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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resnapshotted the ARM test. we'll see if it builds.

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pinged @digantdesai for advice on how to proceed with ARM failures

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

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@zingo

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

@swolchok
swolchok merged commit 9eea1f1 into mainApr 4, 2025
@swolchok
swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
@swolchok@kirklandsign
Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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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"; var __re = new RegExp('^' + "youtube\\.com" + '
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Bump PyTorch pin to 2025-03-25 - #9578

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swolchok merged 16 commits into
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Bump PyTorch pin to 2025-03-25#9578
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84778c7
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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

⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

@swolchok
Update
aafeb54
[ghstack-poisoned]
@swolchok
Update
9f49022
[ghstack-poisoned]
@swolchok
Update
89c4760
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dd30cfa
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2c5ee5f
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Update
9a211b6
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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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resnapshotted the ARM test. we'll see if it builds.

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pinged @digantdesai for advice on how to proceed with ARM failures

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

@zingo

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@swolchok
Update
f78320d
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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

@swolchok
rebase
a37193c
[ghstack-poisoned]
@zingo

zingo commented Apr 3, 2025•
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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

@zingo

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

@swolchok
swolchok merged commit 9eea1f1 into mainApr 4, 2025
@swolchok
swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
@swolchok@kirklandsign
Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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, '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('^' + ".*" + '
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Bump PyTorch pin to 2025-03-25 - #9578

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Bump PyTorch pin to 2025-03-25#9578
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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

⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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resnapshotted the ARM test. we'll see if it builds.

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pinged @digantdesai for advice on how to proceed with ARM failures

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

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swolchok merged commit 9eea1f1 into mainApr 4, 2025
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swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
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Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
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kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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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"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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Bump PyTorch pin to 2025-03-25 - #9578

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Bump PyTorch pin to 2025-03-25#9578
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Stack from ghstack (oldest at bottom):

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

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Update
aafeb54
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89c4760
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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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resnapshotted the ARM test. we'll see if it builds.

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pinged @digantdesai for advice on how to proceed with ARM failures

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

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rebase
a37193c
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@zingo

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

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Just merged #9898

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

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swolchok merged commit 9eea1f1 into mainApr 4, 2025
@swolchok
swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
@swolchok@kirklandsign
Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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Bump PyTorch pin to 2025-03-25 - #9578

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Bump PyTorch pin to 2025-03-25#9578
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9578

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

⏳ 1 Pending, 1 Unrelated Failure

As of commit e221434 with merge base c70c208 (image):

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

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Can we do this after our branch cut on Wednesday 6pm?

The reason is that 3-12 is the RC candidate for PT2.7 - anything after that is in the PT2.8

Otherwise, we would have to go back and forth, instead of monotonically increasing the nightly.

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Unfortunately, this is the downside of delaying the branch cut and diverging from pytorch timeline

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Update
aafeb54
[ghstack-poisoned]
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9f49022
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89c4760
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dd30cfa
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Base automatically changed from gh/swolchok/393/head to mainMarch 26, 2025 20:57
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@mergennachin the branch is cut now, right?

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Thank you for your patience, we can move forward now that its post branch cut

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cc @metascroy

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looks like unittest-arm failure are new, CC @digantdesai

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resnapshotted the ARM test. we'll see if it builds.

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pinged @digantdesai for advice on how to proceed with ARM failures

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We have looked into this and have some fixes in the Arm delegate in the works to handle this, hopefully it will be ready tomorrow.

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

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rebase
a37193c
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@zingo

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Fix that hopefully handled the Arm backend problems merged to main e.g. #9834

@zingo still one failure on unittest-arm:

FAILED backends/arm/test/models/test_torch_functions.py::test_torch_fns_BI[t] - RuntimeError: Unknown operator <EdgeOpOverload: quantized_decomposed.quantize_per_tensor.default>: schema = quantized_decomposed::quantize_per_tensor(Tensor input, float scale, int zero_point, int quant_min, int quant_max, ScalarType dtype) -> Tensor for TOSA : TOSA-0.80+BI

Sorry we missed that, for some reason that one didn't give us problem in the internal testing. There is a new fix cooking that hopefully be uploaded tomorrow.

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Just merged #9898

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[ghstack-poisoned]
@swolchok

swolchok commented Apr 4, 2025

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test-qnn-model is failing on main, test-llava-runner-linux failure looks like a flake, retrying

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swolchok merged commit 9eea1f1 into mainApr 4, 2025
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swolchok deleted the gh/swolchok/394/head branch April 4, 2025 19:26
kirklandsign pushed a commit that referenced this pull request Apr 11, 2025
@swolchok@kirklandsign
Bump PyTorch pin to 2025-03-25 (#9578)
c1a99f4
Found release from
https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
kedarnath03 pushed a commit to kedarnath03/executorch that referenced this pull request Jun 25, 2025
@swolchok
Bump PyTorch pin to 2024-03-25
43158b5
Found release from https://hud2.pytorch.org/hud/pytorch/pytorch/nightly/0 .
ghstack-source-id: fd7a347
ghstack-comment-id: 2751751034
Pull Request resolved: pytorch/executorch#9578
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