https://github.com/cg-tuwien/ppsurf
Tip revision: 060675dce56a49dbee8ea74301740eaaefce33ba authored by Philipp Erler on 04 April 2024, 08:31:57 UTC
Update README.md with new micromamba URL and command, update bibtex
Update README.md with new micromamba URL and command, update bibtex
Tip revision: 060675d
full_run_pps_mini.py
# a short run of PPSurf for testing, debugging and profiling
# profiling with tree visualization
# pip install snakeviz
# https://jiffyclub.github.io/snakeviz/
# python -m cProfile -o pps.prof pps.py
# snakeviz pps.prof
import os
from source.base.mp import get_multi_gpu_params
if __name__ == '__main__':
python_call = 'python'
main_cmd = 'pps.py'
name = 'ppsurf_mini'
version = '0'
# on_server = False
debug = ''
print_config = ''
# uncomment for debugging
# debug += '--debug True'
# print_config += '--print_config'
# python_call += ' -m cProfile -o pps.prof' # uncomment for profiling
main_cmd = python_call + ' ' + main_cmd
cmd_template = '{main_cmd} {sub_cmd} {configs} {debug} {print_config}'
configs = '-c configs/poco.yaml -c configs/ppsurf.yaml {server} -c configs/{name}.yaml'
# training
# configs_train = configs.format(server='-c configs/device_server.yaml' if on_server else '', name=name)
configs_train = configs.format(server=' '.join(get_multi_gpu_params()), name=name)
cmd_train = cmd_template.format(main_cmd=main_cmd, sub_cmd='fit',
configs=configs_train, debug=debug, print_config=print_config)
os.system(cmd_train)
args_no_train = ('--ckpt_path models/{name}/version_{version}/checkpoints/last.ckpt '
'--trainer.logger False ' # comment for tensorboard profiling
'--trainer.devices 1'
).format(name=name, version=version)
configs_no_train = configs.format(server='', name=name)
cmd_template_no_train = cmd_template + ' --data.init_args.in_file {dataset}/testset.txt ' + args_no_train
# testing
cmd_test = cmd_template_no_train.format(main_cmd=main_cmd, sub_cmd='test', configs=configs_no_train,
dataset='datasets/abc_minimal', debug=debug, print_config=print_config)
os.system(cmd_test)
# prediction
datasets = [
'abc_minimal',
# 'abc',
# 'abc_extra_noisy',
# 'abc_noisefree',
# 'real_world',
# 'famous_original', 'famous_noisefree', 'famous_sparse', 'famous_dense', 'famous_extra_noisy',
# 'thingi10k_scans_original', 'thingi10k_scans_noisefree', 'thingi10k_scans_sparse',
# 'thingi10k_scans_dense', 'thingi10k_scans_extra_noisy'
]
# configs_no_train += ' --model.init_args.rec_batch_size 100'
for ds in datasets:
cmd_pred = cmd_template_no_train.format(main_cmd=main_cmd, sub_cmd='predict', configs=configs_no_train,
dataset='datasets/' + ds, debug=debug, print_config=print_config)
# cmd_pred += ' -c configs/profiler.yaml'
cmd_pred += ' --model.init_args.gen_resolution_global 129'
os.system(cmd_pred)