python3.8 /project/DualStyleGAN/run_gan.py
for year in {2004..2013}; do
python /home/janett1005/project/few-shot-gan/dataset_tool.py
create_from_images
/home/janett1005/project/data/tfrecords/$year
/home/janett1005/project/data/crop/merge/$year
--resolution 1024
--partition 1
done
python run_generator.py generate-images --network=/path/to/network/pickle --seeds=0-100
python /project/few-shot-gan/run_training.py
--config=config-ada-sv-flat
--data-dir=/project/data/tfrecord
--dataset-train=/project/data/tfrecord/train/2004_to_2006
--dataset-eval=/project/data/tfrecord/val/2004_to_2006
--resume-pkl-dir=/project/models
--resume-pkl='portrait-pca-000020.pkl'
--total-kimg=12
--metrics=None
gpu_executor.cc:991] could not open file to read NUMA node: /sys/bus/pci/devices/0000:2d:00.0/numa_node Your kernel may have been built without NUMA support.
ass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.