def check_status(): commands = [ "kubectl describe pods", "kubectl get pods --selector app=azure-pytorch-elastic", ] util.run_commands(commands)
def run_job(args): util.install_blobfuse_drivers() commands = [ "kubectl delete -f config/azure-pytorch-elastic.yaml", "kubectl apply -f config/azure-pytorch-elastic.yaml", "kubectl describe pods", "kubectl get pods --selector app=azure-pytorch-elastic", ] util.run_commands(commands)
def main(opts): """ Execute using docopt-mpe options. """ settings = opts.flags return util.run_commands(commands, settings, opts)
def main(opts): """ Execute command. """ settings = opts.flags return util.run_commands(commands, settings, opts)
def main(opts): """ Execute command. """ settings = opts.flags opts.default = 'info' return util.run_commands(commands, settings, opts)
def main(opts): """ Execute command. """ settings = opts.flags opts.default = ['balance', 'verify'] return util.run_commands(commands, settings, opts)
def main(opts): """ Execute command. """ # settings = opts.flags opts.flags.configPath = os.path.expanduser(opts.flags.config) settings = util.init_config(opts.flags.configPath, dict(nodes={}, interfaces={}, domain={}), opts.flags) opts.default = "info" return util.run_commands(commands, settings, opts)
def main(opts): """ Execute command. """ api_keys = get_keys_from_env() opts.api = twitter.Api(**api_keys) if opts.flags.cache_timeout != 60: opts.api.SetCacheTimeout(opts.flags.cache_timeout) return util.run_commands(commands, opts.flags, opts)
def main(opts): """ Execute command. """ settings = opts.flags if not re.match(r'^[a-z][a-z]*://', settings.dbref): settings.dbref = 'sqlite:///' + os.path.expanduser(settings.dbref) opts.default = 'info' return util.run_commands(commands, settings, opts)
def main(opts): """ Execute command. """ #config = confparse.expand_config_path('domain.rc') opts.flags.configPath = os.path.expanduser(opts.flags.config) settings = util.init_config(opts.flags.configPath, dict( nodes = {}, interfaces = {}, domain = {} ), opts.flags) opts.default = 'info' return util.run_commands(commands, settings, opts)
def capture(self): cmds = self.get_infer_commands(util.get_build_output(self.build_cmd)) return util.run_commands(cmds)
def get_logs(): util.run_commands(["kubectl logs --selector app=azure-pytorch-elastic "])