CoreML Export Error: export failure: 'torch._C.Node' object has no attribute 'ival'

[samygarg]

🐛 Bug

I am trying to export the default trained YOLOv5 Model as given here to CoreML but getting an error on both Colab as well as my laptop:

CoreML: export failure: 'torch._C.Node' object has no attribute 'ival'

To Reproduce (REQUIRED)

Follow the steps mentioned here.

Expected behavior

Export the CoreML model successfully.

Environment

Colab and Macbook Pro 13 inch 2019.

[github-actions]

👋 Hello @samygarg, thank you for your interest in 🚀 YOLOv5! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

Environments

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Status

If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training (train.py), testing (test.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit.

[meng1994412]

I have the same issue.

The environment I have is:
OS: Ubuntu 18.04
Packages (by using pip install -r requirement.txt):
torch==1.8.1
torchvision==0.9.1
coremltools==4.1
onnx==1.9.0
scikit-learn==0.19.2

[haynec]

I also get the same issue.

The environment I have is:
OS: Ubuntu 20.04
Packages (by using pip install -r requirement.txt):
torch==1.8.1
torchvision==0.9.1
coremltools==4.1
onnx==1.9.0
scikit-learn==0.19.2

[JorgeCeja]

Hey everyone, it appears that optimize_for_mobile from torch is what causes the incompatibility issue with coremltools.

The solution is to comment the line before export. Optimally it should be an arg option, pull request anyone?

yolov5/models/export.py

Line 72 in 33712d6

ts = optimize_for_mobile(ts) # https://pytorch.org/tutorials/recipes/script_optimized.html

[haynec]

Thanks @JorgeCeja, that solution worked for me.

[samygarg]

@JorgeCeja It solved the original issue but it still doesn't work. Tried on colab as well as macbook pro.

Here's what I am getting:

CoreML: starting export with coremltools 4.1...
Tuple detected at graph output. This will be flattened in the converted model.
Converting graph.
Adding op '1' of type const
Adding op '2' of type const
...
Converting op 728 : sub
Adding op '728' of type sub
Converting op 729 : add
Adding op '729' of type add
Converting op 730 : select
Converting Frontend ==> MIL Ops:  78% 545/695 [00:00<00:00, 933.85 ops/s] 
CoreML: export failure:

[meng1994412]

Thanks @JorgeCeja, the solution you provided worked for me.

[glemarivero]

Hey everyone, it appears that optimize_for_mobile from torch is what causes the incompatibility issue with coremltools.

The solution is to comment the line before export. Optimally it should be an arg option, pull request anyone?

yolov5/models/export.py

Line 72 in 33712d6

ts = optimize_for_mobile(ts) # https://pytorch.org/tutorials/recipes/script_optimized.html

@JorgeCeja Can you share your environment? This change fixed the original issue, but I still face the same issue as @samygarg

[pocketpixels]

It seems CoreML export is broken in multiple ways currently. The export did work with the above change until very recently. However only when not specifying --grid, which meant that the Detect module did not get exported. When trying to export with --grid you would get the same export failure at op 730.
Commit b292837 from issue #2982 (from May 3rd) changed the export implementation to export the Detect module by default.

[pocketpixels]

After trying many different previous commits (and different Pytorch versions) today my impression is that exporting the whole network including the Detect module to CoreML probably never worked? If anyone knows of a version/commit (and environment) where it did work I would love to know.

[zhedahe]

@JorgeCeja It solved the original issue but it still doesn't work. Tried on colab as well as macbook pro.

Here's what I am getting:

CoreML: starting export with coremltools 4.1...
Tuple detected at graph output. This will be flattened in the converted model.
Converting graph.
Adding op '1' of type const
Adding op '2' of type const
...
Converting op 728 : sub
Adding op '728' of type sub
Converting op 729 : add
Adding op '729' of type add
Converting op 730 : select
Converting Frontend ==> MIL Ops:  78% 545/695 [00:00<00:00, 933.85 ops/s] 
CoreML: export failure:

I meet the same question, my enviroment:
OS: Ubuntu 16.04
Packages (by using pip install -r requirement.txt):
torch==1.8.1
torchvision==0.9.1
coremltools==4.1
onnx==1.9.0
scikit-learn==0.19.2

error message:
……
Converting op 725 : constant
Adding op '725' of type const
Converting op 726 : mul
Adding op '726' of type mul
Converting op 727 : constant
Adding op '727' of type const
Converting op 728 : sub
Adding op '728' of type sub
Converting op 729 : add
Adding op '729' of type add
Converting op 730 : select
Converting Frontend ==> MIL Ops: 87%|███▍| 604/695 [00:00<00:00, 1149.09 ops/s]
CoreML: export failure:

hope somebody gave advice, thanks!

[glenn-jocher]

@meng1994412 @haynec @JorgeCeja @samygarg good news 😃! Your original issue may now been fixed ✅ in PR #3055. Note that this does not solve CoreML export completely, but it should resolve the original error message in this issue.

To receive this update you can:

• git pull from within your yolov5/ directory
• git clone https://github.com/ultralytics/yolov5 again
• Force-reload PyTorch Hub: model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• View our updated notebooks:

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!