import argparse
parser = argparse.ArgumentParser(description='Tangent convolutions')
parser.add_argument('config', type=str,  metavar='N', help='config json file')
parser.add_argument('--precompute', action="store_true", help='do precomputation')
parser.add_argument('--train', action="store_true", help='do training network')
parser.add_argument('--test', action="store_true", help='do testing network')
parser.add_argument('--extrapolate', action="store_true", help='do extrapolate for the evaluation')
parser.add_argument('--evaluate', action="store_true", help='do evaluation')
args = parser.parse_args()

# reading configuration files
import os, sys
sys.path.append('util')
from config_reader import *
config = config_reader(args.config)

# do actions
if args.precompute:
  from precompute import *
  print(":: precompute")
  run_precompute(config)

if args.train:
  from model import *
  print(":: training")
  run_net(config, "train")

if args.test:
  from model import *
  print(":: testing")
  run_net(config, "test")

if args.extrapolate:
  from extrapolate import *
  print(":: extrapolate")
  run_extrapolate_labels(config)

if args.evaluate:
  from eval import *
  print(":: evaluate")
  run_eval(config)

8576d87b5fc48195ffc89518dd447dea6eceb979
<mask token>

<mask token>
parser.add_argument('config', type=str, metavar='N', help='config json file')
parser.add_argument('--precompute', action='store_true', help=
    'do precomputation')
parser.add_argument('--train', action='store_true', help='do training network')
parser.add_argument('--test', action='store_true', help='do testing network')
parser.add_argument('--extrapolate', action='store_true', help=
    'do extrapolate for the evaluation')
parser.add_argument('--evaluate', action='store_true', help='do evaluation')
<mask token>
sys.path.append('util')
<mask token>
if args.precompute:
    from precompute import *
    print(':: precompute')
    run_precompute(config)
if args.train:
    from model import *
    print(':: training')
    run_net(config, 'train')
if args.test:
    from model import *
    print(':: testing')
    run_net(config, 'test')
if args.extrapolate:
    from extrapolate import *
    print(':: extrapolate')
    run_extrapolate_labels(config)
if args.evaluate:
    from eval import *
    print(':: evaluate')
    run_eval(config)

<mask token>
parser = argparse.ArgumentParser(description='Tangent convolutions')
parser.add_argument('config', type=str, metavar='N', help='config json file')
parser.add_argument('--precompute', action='store_true', help=
    'do precomputation')
parser.add_argument('--train', action='store_true', help='do training network')
parser.add_argument('--test', action='store_true', help='do testing network')
parser.add_argument('--extrapolate', action='store_true', help=
    'do extrapolate for the evaluation')
parser.add_argument('--evaluate', action='store_true', help='do evaluation')
args = parser.parse_args()
<mask token>
sys.path.append('util')
<mask token>
config = config_reader(args.config)
if args.precompute:
    from precompute import *
    print(':: precompute')
    run_precompute(config)
if args.train:
    from model import *
    print(':: training')
    run_net(config, 'train')
if args.test:
    from model import *
    print(':: testing')
    run_net(config, 'test')
if args.extrapolate:
    from extrapolate import *
    print(':: extrapolate')
    run_extrapolate_labels(config)
if args.evaluate:
    from eval import *
    print(':: evaluate')
    run_eval(config)

import argparse
parser = argparse.ArgumentParser(description='Tangent convolutions')
parser.add_argument('config', type=str, metavar='N', help='config json file')
parser.add_argument('--precompute', action='store_true', help=
    'do precomputation')
parser.add_argument('--train', action='store_true', help='do training network')
parser.add_argument('--test', action='store_true', help='do testing network')
parser.add_argument('--extrapolate', action='store_true', help=
    'do extrapolate for the evaluation')
parser.add_argument('--evaluate', action='store_true', help='do evaluation')
args = parser.parse_args()
import os, sys
sys.path.append('util')
from config_reader import *
config = config_reader(args.config)
if args.precompute:
    from precompute import *
    print(':: precompute')
    run_precompute(config)
if args.train:
    from model import *
    print(':: training')
    run_net(config, 'train')
if args.test:
    from model import *
    print(':: testing')
    run_net(config, 'test')
if args.extrapolate:
    from extrapolate import *
    print(':: extrapolate')
    run_extrapolate_labels(config)
if args.evaluate:
    from eval import *
    print(':: evaluate')
    run_eval(config)

import argparse
parser = argparse.ArgumentParser(description='Tangent convolutions')
parser.add_argument('config', type=str,  metavar='N', help='config json file')
parser.add_argument('--precompute', action="store_true", help='do precomputation')
parser.add_argument('--train', action="store_true", help='do training network')
parser.add_argument('--test', action="store_true", help='do testing network')
parser.add_argument('--extrapolate', action="store_true", help='do extrapolate for the evaluation')
parser.add_argument('--evaluate', action="store_true", help='do evaluation')
args = parser.parse_args()

# reading configuration files
import os, sys
sys.path.append('util')
from config_reader import *
config = config_reader(args.config)

# do actions
if args.precompute:
  from precompute import *
  print(":: precompute")
  run_precompute(config)

if args.train:
  from model import *
  print(":: training")
  run_net(config, "train")

if args.test:
  from model import *
  print(":: testing")
  run_net(config, "test")

if args.extrapolate:
  from extrapolate import *
  print(":: extrapolate")
  run_extrapolate_labels(config)

if args.evaluate:
  from eval import *
  print(":: evaluate")
  run_eval(config)
