def main():
setup_logging()
config_help = "\n\nConfig parameters:\n\n" + "\n".join(ConfigSchema.help())
parser = argparse.ArgumentParser(
epilog=config_help,
# Needed to preserve line wraps in epilog.
formatter_class=argparse.RawDescriptionHelpFormatter,
)
parser.add_argument("config", help="Path to config file")
parser.add_argument("-p", "--param", action="append", nargs="*")
parser.add_argument(
"--rank",
type=int,
default=SINGLE_TRAINER,
help="For multi-machine, this machine's rank",
)
opt = parser.parse_args()
loader = ConfigFileLoader()
config = loader.load_config(opt.config, opt.param)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
train(config, rank=opt.rank, subprocess_init=subprocess_init)
def main():
setup_logging()
config_help = '\n\nConfig parameters:\n\n' + '\n'.join(ConfigSchema.help())
parser = argparse.ArgumentParser(
epilog=config_help,
# Needed to preserve line wraps in epilog.
formatter_class=argparse.RawDescriptionHelpFormatter,
)
parser.add_argument('config', help="Path to config file")
parser.add_argument('-p', '--param', action='append', nargs='*')
parser.add_argument('--rank',
type=int,
default=0,
help="For multi-machine, this machine's rank")
opt = parser.parse_args()
if opt.param is not None:
overrides = chain.from_iterable(opt.param) # flatten
else:
overrides = None
loader = ConfigFileLoader()
config = loader.load_config(opt.config, overrides)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
train(config, rank=Rank(opt.rank), subprocess_init=subprocess_init)
def main():
setup_logging()
parser = argparse.ArgumentParser(description='Example on FB15k')
parser.add_argument('--config', default=DEFAULT_CONFIG,
help='Path to config file')
parser.add_argument('-p', '--param', action='append', nargs='*')
parser.add_argument('--data_dir', type=Path, default='data',
help='where to save processed data')
parser.add_argument('--no-filtered', dest='filtered', action='store_false',
help='Run unfiltered eval')
args = parser.parse_args()
if args.param is not None:
overrides = chain.from_iterable(args.param) # flatten
else:
overrides = None
# download data
data_dir = args.data_dir
fpath = download_url(FB15K_URL, data_dir)
extract_tar(fpath)
print('Downloaded and extracted file.')
loader = ConfigFileLoader()
config = loader.load_config(args.config, overrides)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
input_edge_paths = [data_dir / name for name in FILENAMES]
output_train_path, output_valid_path, output_test_path = config.edge_paths
convert_input_data(
config.entities,
config.relations,
config.entity_path,
config.edge_paths,
input_edge_paths,
lhs_col=0,
rhs_col=2,
rel_col=1,
dynamic_relations=config.dynamic_relations,
)
train_config = attr.evolve(config, edge_paths=[output_train_path])
train(train_config, subprocess_init=subprocess_init)
relations = [attr.evolve(r, all_negs=True) for r in config.relations]
eval_config = attr.evolve(
config, edge_paths=[output_test_path], relations=relations, num_uniform_negs=0)
if args.filtered:
filter_paths = [output_test_path, output_valid_path, output_train_path]
do_eval(
eval_config,
evaluator=FilteredRankingEvaluator(eval_config, filter_paths),
subprocess_init=subprocess_init,
)
else:
do_eval(eval_config, subprocess_init=subprocess_init)
def main():
setup_logging()
parser = argparse.ArgumentParser(description='Example on Livejournal')
parser.add_argument('--config',
default=DEFAULT_CONFIG,
help='Path to config file')
parser.add_argument('-p', '--param', action='append', nargs='*')
parser.add_argument('--data_dir',
type=Path,
default='data',
help='where to save processed data')
args = parser.parse_args()
if args.param is not None:
overrides = chain.from_iterable(args.param) # flatten
else:
overrides = None
# download data
data_dir = args.data_dir
data_dir.mkdir(parents=True, exist_ok=True)
fpath = download_url(URL, data_dir)
fpath = extract_gzip(fpath)
print('Downloaded and extracted file.')
# random split file for train and test
random_split_file(fpath)
loader = ConfigFileLoader()
config = loader.load_config(args.config, overrides)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
edge_paths = [data_dir / name for name in FILENAMES.values()]
convert_input_data(
config.entities,
config.relations,
config.entity_path,
edge_paths,
lhs_col=0,
rhs_col=1,
rel_col=None,
dynamic_relations=config.dynamic_relations,
)
train_path = [str(convert_path(data_dir / FILENAMES['train']))]
train_config = attr.evolve(config, edge_paths=train_path)
train(train_config, subprocess_init=subprocess_init)
eval_path = [str(convert_path(data_dir / FILENAMES['test']))]
eval_config = attr.evolve(config, edge_paths=eval_path)
do_eval(eval_config, subprocess_init=subprocess_init)
def main():
setup_logging()
parser = argparse.ArgumentParser(description='Example on Livejournal')
parser.add_argument('--config',
default=DEFAULT_CONFIG,
help='Path to config file')
parser.add_argument('-p', '--param', action='append', nargs='*')
parser.add_argument('--data_dir',
type=Path,
default='data',
help='where to save processed data')
args = parser.parse_args()
# download data
data_dir = args.data_dir
data_dir.mkdir(parents=True, exist_ok=True)
fpath = download_url(URL, data_dir)
fpath = extract_gzip(fpath)
print('Downloaded and extracted file.')
# random split file for train and test
random_split_file(fpath)
loader = ConfigFileLoader()
config = loader.load_config(args.config, args.param)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
input_edge_paths = [data_dir / name for name in FILENAMES]
output_train_path, output_test_path = config.edge_paths
convert_input_data(
config.entities,
config.relations,
config.entity_path,
config.edge_paths,
input_edge_paths,
TSVEdgelistReader(lhs_col=0, rhs_col=1, rel_col=None),
dynamic_relations=config.dynamic_relations,
)
train_config = attr.evolve(config, edge_paths=[output_train_path])
train(train_config, subprocess_init=subprocess_init)
eval_config = attr.evolve(config, edge_paths=[output_test_path])
do_eval(eval_config, subprocess_init=subprocess_init)
def main():
# Late import to avoid circular dependency.
from torchbiggraph.util import set_logging_verbosity, setup_logging
setup_logging()
parser = argparse.ArgumentParser()
parser.add_argument('config', help="Path to config file")
parser.add_argument('query', help="Name of param to retrieve")
parser.add_argument('-p', '--param', action='append', nargs='*')
opt = parser.parse_args()
if opt.param is not None:
overrides = chain.from_iterable(opt.param) # flatten
else:
overrides = None
loader = ConfigFileLoader()
config = loader.load_config(opt.config, overrides)
set_logging_verbosity(config.verbose)
print(config[opt.query])
def main():
setup_logging()
config_help = '\n\nConfig parameters:\n\n' + '\n'.join(ConfigSchema.help())
parser = argparse.ArgumentParser(
epilog=config_help,
# Needed to preserve line wraps in epilog.
formatter_class=argparse.RawDescriptionHelpFormatter,
)
parser.add_argument('config', help="Path to config file")
parser.add_argument('-p', '--param', action='append', nargs='*')
opt = parser.parse_args()
loader = ConfigFileLoader()
config = loader.load_config(opt.config, opt.param)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
do_eval(config, subprocess_init=subprocess_init)
def main():
setup_logging()
parser = argparse.ArgumentParser(description="Example on FB15k")
parser.add_argument("--config",
default=DEFAULT_CONFIG,
help="Path to config file")
parser.add_argument("-p", "--param", action="append", nargs="*")
parser.add_argument("--data_dir",
type=Path,
default="data",
help="where to save processed data")
parser.add_argument(
"--no-filtered",
dest="filtered",
action="store_false",
help="Run unfiltered eval",
)
args = parser.parse_args()
# download data
data_dir = args.data_dir
fpath = download_url(FB15K_URL, data_dir)
extract_tar(fpath)
print("Downloaded and extracted file.")
loader = ConfigFileLoader()
config = loader.load_config(args.config, args.param)
set_logging_verbosity(config.verbose)
subprocess_init = SubprocessInitializer()
subprocess_init.register(setup_logging, config.verbose)
subprocess_init.register(add_to_sys_path, loader.config_dir.name)
input_edge_paths = [data_dir / name for name in FILENAMES]
output_train_path, output_valid_path, output_test_path = config.edge_paths
convert_input_data(
config.entities,
config.relations,
config.entity_path,
config.edge_paths,
input_edge_paths,
TSVEdgelistReader(lhs_col=0, rhs_col=2, rel_col=1),
dynamic_relations=config.dynamic_relations,
)
train_config = attr.evolve(config, edge_paths=[output_train_path])
train(train_config, subprocess_init=subprocess_init)
relations = [attr.evolve(r, all_negs=True) for r in config.relations]
eval_config = attr.evolve(config,
edge_paths=[output_test_path],
relations=relations,
num_uniform_negs=0)
if args.filtered:
filter_paths = [output_test_path, output_valid_path, output_train_path]
do_eval(
eval_config,
evaluator=FilteredRankingEvaluator(eval_config, filter_paths),
subprocess_init=subprocess_init,
)
else:
do_eval(eval_config, subprocess_init=subprocess_init)