Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248

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fix-llava-runner-timeout
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Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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Fixes#8180

I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.

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@huydhnhuydhn changed the title Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve

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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve

Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.

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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve

Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58

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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988

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huydhn merged commit 524ec78 into mainFeb 10, 2025
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huydhn deleted the fix-llava-runner-timeout branch February 10, 2025 02:27
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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true

@swolchokswolchok mentioned this pull request Feb 10, 2025
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Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
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@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
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huydhn merged 15 commits into
mainfrom 
fix-llava-runner-timeout
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Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
huydhn merged 15 commits into
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fix-llava-runner-timeout
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8248
Note: Links to docs will display an error until the docs builds have been completed.
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Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
@swolchokswolchok
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@swolchok
Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
@github-actionsgithub-actionsBot
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@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
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huydhn merged 15 commits into
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fix-llava-runner-timeout
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Merged
Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8248
Note: Links to docs will display an error until the docs builds have been completed.
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Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
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@swolchok
Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
@github-actionsgithub-actionsBot
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@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
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huydhn merged 15 commits into
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fix-llava-runner-timeout
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Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
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@swolchok
Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
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@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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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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Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
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fix-llava-runner-timeout
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Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8248
Note: Links to docs will display an error until the docs builds have been completed.
✅ No Failures
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Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
@huydhn
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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
@huydhn
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
@huydhn
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
@huydhn
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fix-llava-runner-timeout

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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
@swolchokswolchok
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that referenced
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@swolchok
Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
@github-actionsgithub-actionsBot
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Feb 11, 2025

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@huydhnhuydhn
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@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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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('^' + ".*" + '

Skip to content
Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
Merged
huydhn merged 15 commits into
mainfrom 
fix-llava-runner-timeout
Feb 10, 2025
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Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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fix-llava-runner-timeout
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8248
Note: Links to docs will display an error until the docs builds have been completed.
✅ No Failures
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Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
@huydhn
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
@huydhn
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fix-llava-runner-timeout

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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
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@swolchok
Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
@github-actionsgithub-actionsBot
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@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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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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Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
Merged
huydhn merged 15 commits into
mainfrom 
fix-llava-runner-timeout
Feb 10, 2025
Merged
Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8248
Note: Links to docs will display an error until the docs builds have been completed.
✅ No Failures
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
@huydhn
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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
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February 9, 2025 19:59
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
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fix-llava-runner-timeout

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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
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Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
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Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
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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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Install mkl for PyTorch and libjpeg/libpng for TorchVision - #8248
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Install mkl for PyTorch and libjpeg/libpng for TorchVision#8248
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Fixes#8180
I should have caught this earlier that we didn't have mkl here, so PyTorch performance on x86 CPU suffered.
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🔗 Helpful Links
🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8248
Note: Links to docs will display an error until the docs builds have been completed.
✅ No Failures
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Install libjpeg and libpng for TorchVisionInstall mkl for PyTorch and libjpeg/libpng for TorchVisionFeb 6, 2025
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looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
@huydhn
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commented
Feb 7, 2025

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looks like you've got conda library problems but this is clearly an accept contingent on you seeing llava-runner job improve
Let me look more into that conda issue. This is rather unexpected, I have done a rebase, so the failure is legit.
@huydhn
huydhn
commented
Feb 9, 2025

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ContributorAuthor
looks like you've got conda library problems but this is clearly a PR I should accept, contingent on you seeing llava-runner job improve
Just FYI, the linking error is from this hack https://github.com/pytorch/executorch/blob/main/.ci/docker/common/install_conda.sh#L46-L58
@huydhn
huydhn
marked this pull request as ready for review
February 9, 2025 19:59
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The run time is around 1h20m now https://github.com/pytorch/executorch/actions/runs/13229090225/job/36927181503 v.s 2h30m https://github.com/pytorch/executorch/actions/runs/13213708877/job/36890417988
@huydhn
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merged commit 524ec78
into
mainFeb 10, 2025
@huydhn
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fix-llava-runner-timeout

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February 10, 2025 02:27
@swolchok
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eval_llama-mmlu seems to have gone from 1.9h to under 9 minutes: https://hud.pytorch.org/hud/pytorch/executorch/main/1?per_page=50&name_filter=mmlu&mergeLF=true
@swolchokswolchok
mentioned this pull request
Feb 10, 2025
 Merged

swolchok added a commit
that referenced
this pull request
Feb 10, 2025
@swolchok
Lower timeout for llava-runner and eval_llama-mmlu jobs again
878f14c
#8173 raised these timeouts. Now that #8248 has landed to fix#8180, we should be able to lower them again. (I'm sending this early so I don't forget; double-check llava-runner running time)
ghstack-source-id: cb4c169
ghstack-comment-id: 2648474106
Pull Request resolved: #8339
@github-actionsgithub-actionsBot
mentioned this pull request
Feb 11, 2025

Open

@huydhnhuydhn
mentioned this pull request
Feb 12, 2025
 Merged

swolchok pushed a commit
that referenced
this pull request
Feb 12, 2025
@huydhn
Fix multiple find_package(Torch) calls (#8407)
1308d4d
While debugging the build issue on #8322 w.r.t mkl, I undercover a complex interaction between #8322, #8248 (to install mkl), and https://github.com/pytorch/pytorch/blob/main/cmake/public/mkl.cmake from PyTorch. The error is as follows:
```
CMake Error at /opt/conda/envs/py_3.10/lib/cmake/mkl/MKLConfig.cmake:744 (add_library): <-- This file comes from conda mkl
add_library cannot create imported target "MKL::MKL" because another target
with the same name already exists.
Call Stack (most recent call first):
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) <-- this is from PyTorch
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:106 (include)
/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package)
CMakeLists.txt:753 (find_package)
```
The conclusion is that, with mkl installed, there should be just one `find_package(Torch)` call because the mkl target is defined globally. The `torch` target, on the other hand, is only defined locally.
So, this change adds `if(NOT TARGET torch)` check to only call `find_package(Torch)` if needed.
### Testing
The change on top of #8322 looks like this f705b01https://github.com/pytorch/executorch/actions/runs/13278590926?pr=8399
@github-actionsgithub-actionsBot
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