#!/usr/bin/env python3
#
# Reverse : Generate an indented asm code (pseudo-C) with colored syntax.
# Copyright (C) 2015 Joel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
from lib import reverse, parse_args
if __name__ == '__main__':
ctx = parse_args()
if ctx.interactive:
from lib.interactive import Interactive
i = Interactive(ctx)
elif ctx.filename is not None:
reverse(ctx)
import torch.optim as optim
import torch.nn.functional as F
GAMMA = 0.99
BATCH_SIZE = 64
LR_ACTS = 1e-4
LR_VALS = 1e-4
REPLAY_SIZE = 100000
REPLAY_INITIAL = 10000
SAC_ENTROPY_ALPHA = 0.1
if __name__ == "__main__":
parser = make_parser(test_iters=10000)
args, device, save_path, test_env, maxeps, maxsec = parse_args(
parser, "sac")
env = make_env(args)
net_act, net_crt = make_nets(args, env, device)
twinq_net = model.ModelSACTwinQ(env.observation_space.shape[0],
env.action_space.shape[0]).to(device)
print(twinq_net)
tgt_net_crt = ptan.agent.TargetNet(net_crt)
writer = SummaryWriter(comment="-sac_" + args.name)
agent = model.AgentDDPG(net_act, device=device)
exp_source = ptan.experience.ExperienceSourceFirstLast(env,
agent,
#possible argv
c = ['--corpora']
m = ['--mini']
v = ['--vectorize']
s = ['--svm', '--classify']
p = ['--parse']
a = ['--all']
d = ['--delete', '--clean']
#get argv
argv = sys.argv[1:]
if not len(argv): #make --all the default option
argv += a
if not parse_args(argv, c + m + v + s + p + a + d): #invalid option
print('Please select a valid option.')
#exec scripts
if parse_args(argv, c + a):
from scripts import format_bnc, format_wiki
if parse_args(argv, m + a):
from scripts import mini_corpora
if parse_args(argv, v + a):
from scripts import vectorize
if parse_args(argv, s + a):
os.makedirs(Svm.svmdir, exist_ok=True)
os.system('python3 -u scripts/classify.py > ' + \
f'{Svm.svmdir}{Svm.desc}.txt')
if parse_args(argv, p + a):
from scripts import parse
file_name = Path.joinpath(DIR_PROJECT_FOLDER, "nodemon.json")
create_from_template("cpy_nodemon_json", file_name, {"project": project})
create_empty_files(DIR_PROJECT_MAIN, ['__init__.py'])
if pip:
print("Init pip environment")
os.system("pipenv install autopep8 pyinstaller ptpython --dev")
os.system("pipenv install requests python-dotenv")
if args.flaskapp:
install_flask_app_dependencies()
if args.packages:
os.system('pipenv install ' + args.packages)
add_git(project)
if open_vs_code:
os.chdir(DIR_PROJECT_FOLDER)
os.system(f"code . {main_file_name}")
if pip:
os.system(f"pipenv shell")
if __name__ == "__main__":
args = parse_args()
run(pip=args.pipenv)
os.chdir(DIR_PROJECT_PUBLIC_FOLDER)
crap.handle_index_html(DIR_PROJECT_PUBLIC_FOLDER, project_name)
os.chdir(DIR_PROJECT_SRC_FOLDER)
crap.remove_files()
crap.create_app_jsx(DIR_PROJECT_SRC_FOLDER, project_name)
crap.create_index_css(DIR_PROJECT_SRC_FOLDER)
create_empty_files(DIR_PROJECT_SRC_FOLDER, ['App.css'])
os.chdir(DIR_PROJECT_FOLDER)
crap.handle_readme_file(DIR_PROJECT_FOLDER, project_name)
create_empty_files(DIR_PROJECT_FOLDER, ['.env'])
if packages:
os.system('yarn add ' + packages)
# Handle GIT
os.system('echo ".env" >> .gitignore')
os.system('git add .')
os.system('git commit -m "removed crap files to empty project" ')
os.system('code .')
os.system('yarn start')
if __name__ == "__main__":
run(parse_args())
