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module: build/installIssues related to the cmake and buck2 builds, and to installing ExecuTorchIssues related to the cmake and buck2 builds, and to installing ExecuTorchneed-user-inputThe issue needs more information from the reporter before moving forwardThe issue needs more information from the reporter before moving forwardtriagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate moduleThis issue has been looked at a team member, and triaged and prioritized into an appropriate module
Description
Sorry to bother with a minor install issue.
I can install from source on my local machine just fine. However on a Google Cloud machine I have been unable to troubleshoot the following error:
File "/conda/lib/python3.12/site-packages/setuptools/dist.py", line 950, in run_command
super().run_command(command)
File "/conda/lib/python3.12/site-packages/setuptools/_distutils/dist.py", line 973, in run_command
cmd_obj.run()
File "<string>", line 619, in run
File "<string>", line 258, in get_build_type
ValueError: invalid literal for int() with base 10: ''
error: subprocess-exited-with-error
The Google Cloud machine is running Ubuntu 24.04 and I have installed g++ (13.3.0) and clang++ (18.1.3).
For the installation I followed the guide linked below, using a Python 3.10.0 virtual environment. https://pytorch.org/executorch/main/getting-started-setup
I am only wanting to export a pte file for a model that is too large for my local machine. The version available through pip doesn't seem to be able to do this.
Do you have other troubleshooting tips?
digantdesai
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module: build/installIssues related to the cmake and buck2 builds, and to installing ExecuTorchIssues related to the cmake and buck2 builds, and to installing ExecuTorchneed-user-inputThe issue needs more information from the reporter before moving forwardThe issue needs more information from the reporter before moving forwardtriagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate moduleThis issue has been looked at a team member, and triaged and prioritized into an appropriate module