#!/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())