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 "])
