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### Running command:
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###   /Library/Frameworks/R.framework/Resources/bin/R CMD build --keep-empty-dirs --no-resave-data orthos
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* checking for file ‘orthos/DESCRIPTION’ ... OK
* preparing ‘orthos’:
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ...sh: line 1:  2598 Abort trap: 6           '/Library/Frameworks/R.framework/Resources/bin/Rscript' --vanilla --default-packages= -e "tools::buildVignettes(dir = '.', tangle = TRUE)" > '/tmp/RtmpLmsFO4/xshell7003b24b554' 2>&1
 ERROR
--- re-building ‘orthosIntro.Rmd’ using rmarkdown
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:5 out of the last 5 calls to <function Model.make_predict_function.<locals>.predict_function at 0x2b90bc940> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.
WARNING:tensorflow:6 out of the last 6 calls to <function Model.make_predict_function.<locals>.predict_function at 0x2b90bd000> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.
2025-04-01 04:47:51.098 R[2598:339668056] XType: Using static font registry.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
--- finished re-building ‘orthosIntro.Rmd’

pybind11::handle::dec_ref() is being called while the GIL is either not held or invalid. Please see https://pybind11.readthedocs.io/en/stable/advanced/misc.html#common-sources-of-global-interpreter-lock-errors for debugging advice.
If you are convinced there is no bug in your code, you can #define PYBIND11_NO_ASSERT_GIL_HELD_INCREF_DECREFto disable this check. In that case you have to ensure this #define is consistently used for all translation units linked into a given pybind11 extension, otherwise there will be ODR violations.The failing pybind11::handle::dec_ref() call was triggered on a type object.
libc++abi: terminating due to uncaught exception of type std::runtime_error: pybind11::handle::dec_ref() PyGILState_Check() failure.