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[Core ML] Avoid recompiling models when the OS version is not changed #69234

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@xta0 xta0 commented Dec 1, 2021 •
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Stack from ghstack:

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: D32743881

@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
4b39827 
We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
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facebook-github-bot commented Dec 1, 2021 •
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🔗 Helpful links

💊 CI failures summary and remediations

As of commit 6baf496 (more details on the Dr. CI page):

  • 3/3 failures introduced in this PR

🕵️ 1 new failure recognized by patterns

The following CI failures do not appear to be due to upstream breakages:

See GitHub Actions build linux-xenial-py3.6-gcc5.4 / test (backwards_compat, 1, 1, linux.2xlarge) (1/1)

Step: "Test" (full log | diagnosis details | 🔁 rerun)

2021-12-05T00:09:20.5422854Z The PR is introduc...m to confirm whether this change is wanted or not. 
2021-12-05T00:09:20.5406043Z processing existing schema:  text(__torch__.torch.classes.profiling.SourceRef _0) -> (str _0)
2021-12-05T00:09:20.5407332Z processing existing schema:  count(__torch__.torch.classes.profiling.InstructionStats _0) -> (int _0)
2021-12-05T00:09:20.5408782Z processing existing schema:  duration_ns(__torch__.torch.classes.profiling.InstructionStats _0) -> (int _0)
2021-12-05T00:09:20.5410868Z processing existing schema:  source(__torch__.torch.classes.profiling.SourceStats _0) -> (__torch__.torch.classes.profiling.SourceRef _0)
2021-12-05T00:09:20.5412999Z processing existing schema:  line_map(__torch__.torch.classes.profiling.SourceStats _0) -> (Dict(int, __torch__.torch.classes.profiling.InstructionStats) _0)
2021-12-05T00:09:20.5414749Z processing existing schema:  __init__(__torch__.torch.classes.profiling._ScriptProfile _0) -> (NoneType _0)
2021-12-05T00:09:20.5415910Z processing existing schema:  enable(__torch__.torch.classes.profiling._ScriptProfile _0) -> (NoneType _0)
2021-12-05T00:09:20.5417614Z processing existing schema:  disable(__torch__.torch.classes.profiling._ScriptProfile _0) -> (NoneType _0)
2021-12-05T00:09:20.5419668Z processing existing schema:  _dump_stats(__torch__.torch.classes.profiling._ScriptProfile _0) -> (__torch__.torch.classes.profiling.SourceStats[] _0)
2021-12-05T00:09:20.5421501Z processing existing schema:  __init__(__torch__.torch.classes.dist_rpc.WorkerInfo _0, str _1, int _2) -> (NoneType _0)
2021-12-05T00:09:20.5422854Z The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not. 
2021-12-05T00:09:20.5423581Z 
2021-12-05T00:09:20.5423937Z Broken ops: [
2021-12-05T00:09:20.5425311Z 	aten::slow_conv3d_backward.grad_input(Tensor grad_output, Tensor self, Tensor weight, int[3] kernel_size, int[3] stride, int[3] padding, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!))
2021-12-05T00:09:20.5427302Z 	aten::slow_conv3d_backward.output_mask(Tensor grad_output, Tensor self, Tensor weight, int[3] kernel_size, int[3] stride, int[3] padding, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias)
2021-12-05T00:09:20.5428771Z 	aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding) -> (Tensor)
2021-12-05T00:09:20.5430009Z 	aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, *, Tensor(a!) output) -> (Tensor(a!))
2021-12-05T00:09:20.5432027Z 	aten::slow_conv_transpose2d_backward.grad_output(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, int[2] output_padding, int[2] dilation, *, Tensor(a!) grad_input, Tensor(b!) grad_weight, Tensor(c!) grad_bias) -> (Tensor(a!), Tensor(b!), Tensor(c!))
2021-12-05T00:09:20.5434739Z 	aten::slow_conv_transpose2d_backward.output_mask(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, int[2] output_padding, int[2] dilation, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias)
2021-12-05T00:09:20.5435785Z ]
2021-12-05T00:09:20.5436331Z + cleanup

2 failures not recognized by patterns:

Job Step Action
GitHub Actions ios-12-5-1-arm64-coreml / build Build 🔁 rerun
GitHub Actions ios-12-5-1-x86-64-coreml / build Build 🔁 rerun
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pytorch-probot bot commented Dec 1, 2021 •
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CI Flow Status

⚛️ CI Flow

Ruleset - Version: v1
Ruleset - File: https://github.com/pytorch/pytorch/blob/6baf496811e4e20f75184f976321887d367e822e/.github/generated-ciflow-ruleset.json
PR ciflow labels: ciflow/default,ciflow/ios

Workflows Labels (bold enabled) Status
Triggered Workflows
ios-12-5-1-arm64 ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-arm64-coreml ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-arm64-custom-ops ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-arm64-full-jit ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-arm64-metal ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-x86-64 ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-x86-64-coreml ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
ios-12-5-1-x86-64-full-jit ciflow/all, ciflow/ios, ciflow/macos ✅ triggered
linux-bionic-cuda11.5-py3.6-gcc7 ciflow/all, ciflow/cuda, ciflow/default, ciflow/linux ✅ triggered
linux-bionic-py3.6-clang9 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/noarch, ciflow/xla ✅ triggered
linux-vulkan-bionic-py3.6-clang9 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/vulkan ✅ triggered
linux-xenial-cuda11.3-py3.6-gcc7 ciflow/all, ciflow/cuda, ciflow/default, ciflow/linux ✅ triggered
linux-xenial-py3-clang5-mobile-build ciflow/all, ciflow/default, ciflow/linux, ciflow/mobile ✅ triggered
linux-xenial-py3-clang5-mobile-custom-build-static ciflow/all, ciflow/default, ciflow/linux, ciflow/mobile ✅ triggered
linux-xenial-py3.6-clang7-asan ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/sanitizers ✅ triggered
linux-xenial-py3.6-clang7-onnx ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux, ciflow/onnx ✅ triggered
linux-xenial-py3.6-gcc5.4 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux ✅ triggered
linux-xenial-py3.6-gcc7 ciflow/all, ciflow/cpu, ciflow/default, ciflow/linux ✅ triggered
linux-xenial-py3.6-gcc7-bazel-test ciflow/all, ciflow/bazel, ciflow/cpu, ciflow/default, ciflow/linux ✅ triggered
pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single ciflow/all, ciflow/android, ciflow/cpu, ciflow/default, ciflow/linux ✅ triggered
pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-custom-build-single-full-jit ciflow/all, ciflow/android, ciflow/cpu, ciflow/default, ciflow/linux ✅ triggered
win-vs2019-cpu-py3 ciflow/all, ciflow/cpu, ciflow/default, ciflow/win ✅ triggered
win-vs2019-cuda11.3-py3 ciflow/all, ciflow/cuda, ciflow/default, ciflow/win ✅ triggered
Skipped Workflows
caffe2-linux-xenial-py3.6-gcc5.4 ciflow/all, ciflow/cpu, ciflow/linux 🚫 skipped
docker-builds ciflow/all 🚫 skipped
libtorch-linux-bionic-cuda11.5-py3.6-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux 🚫 skipped
libtorch-linux-xenial-cuda10.2-py3.6-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux 🚫 skipped
libtorch-linux-xenial-cuda11.3-py3.6-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux 🚫 skipped
linux-bionic-cuda10.2-py3.9-gcc7 ciflow/all, ciflow/cuda, ciflow/linux, ciflow/slow 🚫 skipped
macos-10-15-py3-arm64 ciflow/all, ciflow/macos 🚫 skipped
macos-10-15-py3-lite-interpreter-x86-64 ciflow/all, ciflow/macos 🚫 skipped
macos-11-py3-x86-64 ciflow/all, ciflow/macos 🚫 skipped
parallelnative-linux-xenial-py3.6-gcc5.4 ciflow/all, ciflow/cpu, ciflow/linux 🚫 skipped
periodic-libtorch-linux-xenial-cuda11.1-py3.6-gcc7 ciflow/all, ciflow/cuda, ciflow/libtorch, ciflow/linux, ciflow/scheduled 🚫 skipped
periodic-linux-xenial-cuda10.2-py3-gcc7-slow-gradcheck ciflow/all, ciflow/cuda, ciflow/linux, ciflow/scheduled, ciflow/slow, ciflow/slow-gradcheck 🚫 skipped
periodic-linux-xenial-cuda11.1-py3.6-gcc7-debug ciflow/all, ciflow/cuda, ciflow/linux, ciflow/scheduled 🚫 skipped
periodic-win-vs2019-cuda11.1-py3 ciflow/all, ciflow/cuda, ciflow/scheduled, ciflow/win 🚫 skipped

You can add a comment to the PR and tag @pytorchbot with the following commands: 
# ciflow rerun, "ciflow/default" will always be added automatically
@pytorchbot ciflow rerun

# ciflow rerun with additional labels "-l <ciflow/label_name>", which is equivalent to adding these labels manually and trigger the rerun
@pytorchbot ciflow rerun -l ciflow/scheduled -l ciflow/slow

For more information, please take a look at the CI Flow Wiki.

@facebook-github-bot facebook-github-bot added cla signed oncall: jit Add this issue/PR to JIT oncall triage queue labels Dec 1, 2021
xta0 added a commit that referenced this pull request Dec 1, 2021
@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
4f5aa7b 
We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

ghstack-source-id: 144433253
Pull Request resolved: #69234
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
7b69b5b 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
5a60aa9 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
xta0 added a commit that referenced this pull request Dec 2, 2021
@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
e4b2612 
Pull Request resolved: #69234

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}
ghstack-source-id: 144563466

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D32743881/)!
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
d2d030a 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
xta0 added a commit that referenced this pull request Dec 2, 2021
@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
672cbc0 
Pull Request resolved: #69234

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}
ghstack-source-id: 144604466

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D32743881/)!
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
a85179f 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
xta0 added a commit that referenced this pull request Dec 3, 2021
@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
5fdd0b9 
Pull Request resolved: #69234

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}
ghstack-source-id: 144677370

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D32743881/)!
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
621b271 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
xta0 added a commit that referenced this pull request Dec 3, 2021
@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
97a5322 
Pull Request resolved: #69234

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}
ghstack-source-id: 144682314

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D32743881/)!
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
88a0640 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
@xta0
Update on "[Core ML] Avoid recompiling models when the OS version is …
6baf496 
…not changed"

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

[ghstack-poisoned]
xta0 added a commit that referenced this pull request Dec 4, 2021
@xta0
[Core ML] Avoid recompiling models when the OS version is not changed
90bf861 
Pull Request resolved: #69234

We don't need to recompile the model if the OS version is not changed. This could save hundreds of ms when loading the model.

{F683788183}
ghstack-source-id: 144784720

Differential Revision: [D32743881](https://our.internmc.facebook.com/intern/diff/D32743881/)

**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D32743881/)!
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suo commented Dec 4, 2021

Looks like this broke ios builds on master, I am reverting: https://hud.pytorch.org/commit/pytorch/pytorch/b97903abb8285cd7d7e102b799f09341b12ac249

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suo commented Dec 4, 2021

@xta0 in the future, if you want to run ios builds on your commit, you can use ciflow, like

@pytorchbot ciflow rerun -l ciflow/ios

@pytorch-probot pytorch-probot bot assigned pytorchbot and unassigned pytorchbot Dec 4, 2021
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suo commented Dec 4, 2021

oh god I made it run

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This pull request has been reverted by 29a45f0. To re-land this change, follow these steps.

@suo suo mentioned this pull request Dec 5, 2021
Closed
@suo suo removed the ciflow/ios label Dec 7, 2021
@facebook-github-bot facebook-github-bot deleted the gh/xta0/145/head branch December 8, 2021 15:15
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This pull request has been reverted by 29a45f0. To re-land this change, follow these steps.

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