type=str,
help="Dataset name",
choices=dbac_data.DB_NAMES)
parser.add_argument('db_path', type=str, help="Dataset directory path")
parser.add_argument('feat_type',
type=str,
help='Feature type',
choices=dbac_feature_ext.FEAT_TYPE)
parser.add_argument('output_path',
type=str,
help="Path to output feature cache dictionary .npz")
parser.add_argument(
'-kwargs',
type=str,
default=None,
help="Kwargs for the feature extractor k1=v1; k2=v2; ...")
parser.add_argument('-gpu_str',
default='0',
type=str,
help='CUDA_VISIBLE_DEVICES')
args = parser.parse_args()
os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu_str
dbac_util.init_logging('_'.join([
os.path.splitext(args.output_path)[0],
'{}.log'.format(datetime.now().strftime("%Y%m%d-%H%M%S"))
]))
logger.info(args)
_extract_features(args.db_name, args.db_path, args.feat_type,
args.output_path, args.kwargs)
type=str,
help='Path to split file to compute split distributions.')
parser_plot.add_argument(
'-comb_file',
type=str,
help='Path to compositions file to compute distributions.')
parser_plot.add_argument('-plot',
default=False,
action='store_true',
help='Generate plot.')
args = parser.parse_args()
if args.cmd_name == 'split':
# set up log system
dbac_util.init_logging('_'.join([
os.path.splitext(args.output_path)[0],
'{}.split.log'.format(datetime.now().strftime("%Y%m%d-%H%M%S"))
]))
logger.info(args)
# Compute dataset splits
logger.info("Computing split for db {} ...".format(args.db_name))
time.sleep(10)
_compute_splits(args.db_name, args.db_path, args.ops, args.output_path,
args.min_per_prim, args.min_per_exp, args.num_exps,
args.min_pos_exp_test, args.nogroup)
elif args.cmd_name == 'comb':
# set up log system
dbac_util.init_logging('_'.join([
os.path.splitext(args.split_file)[0],
'{}.comb.log'.format(datetime.now().strftime("%Y%m%d-%H%M%S"))
]))
logger.info(args)
result_file = os.path.join(output_dir, 'results.npy')
np.save(result_file, report_dic)
logger.info("Results file saved to {}.".format(result_file))
if __name__ == '__main__':
import argparse
from datetime import datetime
import os
parser = argparse.ArgumentParser(description="Script for test Neural Algebra of Classifiers models.", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('db_name', type=str, choices=dbac_data.DB_NAMES, help='Name of the Dataset.')
parser.add_argument('db_dir', type=str, help='Path to the dataset main directory.')
parser.add_argument('split_file', type=str, help='Path to the split json file.')
parser.add_argument('-comb_file', default=None, type=str, help='Path to the compositions json file.')
parser.add_argument('primitives_file', type=str, help='Path to the primitives collection file.')
parser.add_argument('model_name', type=str, choices=dbac_model._MODEL_NAMES, help='Model name.')
parser.add_argument('output_dir', type=str, help='Output directory path.')
parser.add_argument('-model_file', type=str, default=None, help='Path to model file.')
parser.add_argument('-gpu_str', default='0', type=str, help='CUDA_VISIBLE_DEVICES')
parser.add_argument('-kwargs', type=str, default=None, help="Kwargs for the feature extractor k1=v1; k2=v2; ...")
args = parser.parse_args()
print(args)
os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu_str
log_file = os.path.join(args.output_dir, "test_{}.log".format(datetime.now().strftime("%Y%m%d-%H%M%S")))
dbac_util.init_logging(log_file)
logger.info(args)
_test(args.db_name, args.db_dir, args.split_file, args.comb_file, args.primitives_file, args.model_name, args.model_file,
args.output_dir, args.kwargs)