I didn't find any ways to do this.
https://github.com/tjluoma/dropbox-pause-unpause
That seems to be an old plist project with bash scripts for this purpose.
Error
Could not identify NUMA node of platform GPU ID 0, defaulting to 0.
Your kernel may not have been built with NUMA support.
Reproduce
>>> tf.convert_to_tensor([1,2,3])
2022-11-04 14:40:50.905905: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2022-11-04 14:40:50.905986: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
<tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 2, 3], dtype=int32)>
Solution
Tried this
conda install -c apple tensorflow-deps
as suggested here
That introduced yet more errors. I could not import tensorflow as tf anymore.
Jeff Heaton's suggestion (and YAML file) did work.
After creating the environment using his YAML file, the Apple M1 Max was selected as the GPU.
>>> tf.convert_to_tensor([12,3])
Metal device set to: Apple M1 Max
systemMemory: 64.00 GB
maxCacheSize: 24.00 GB
2022-11-04 14:59:41.275014: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2022-11-04 14:59:41.275444: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([12, 3], dtype=int32)>
This page is incomplete
An option is to set CACHE=array on your .env file.
I need to learn why this happens and what other alternatives there are to avoid this error.
This happened to me when installing laravel-geoip
https://github.com/Torann/laravel-geoip/issues/123
It makes sense that you don't want to change your cache type if you're using file or database to array simply to use a function in this package.
Other users recommended to publish tarenn/geoip's config file and disable caching and tagging.
# Publish the configuration file
php artisan vendor:publish --provider="Torann\GeoIP\GeoIPServiceProvider" --tag=config
# Copied File [/vendor/torann/geoip/config/geoip.php] To [/config/geoip.php]
# Publishing complete.
// ...
'cache' => 'none', // defaults to 'all'
// ...
'cache_tags' => [], // defaults to // ['torann-geoip-location']
// ...
Another option is to conditionally set the tag.
// ...
'cache_tags' => env('CACHE_DRIVER') == "array" ? ['torann-geoip-location'] : null,
// ...
