def master_init_slaves(cls,
num_weights,
slaves=(),
timeout=None,
limit=65536,
master_oversees=False,
**kwargs):
"""Initialize proxies for each of the slaves and block on a working
connection.
"""
# Initialize server proxies for the slaves
srv_timeout = 3 * timeout if timeout is not None else 1000
all_machines = [] if master_oversees else [None]
for slave in slaves:
host, port = slave.split(':')
all_machines.append(
jsonrpc.ServerProxy(
jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(host, int(port)),
limit=limit,
timeout=srv_timeout)))
# Block on a working connection to each slave
machine_idx = len(all_machines) - 1
working_connection = False
while not working_connection:
try:
cls.call_slave(all_machines[machine_idx],
'slave_init_weights', num_weights)
working_connection = True
except jsonrpc.RPCTransportError:
print "Waiting to establish connection to slave", slave
time.sleep(10)
return all_machines
def from_server(cls, host_port):
"""Return a proxy Gigaword object with bound methods to
retrieve counts.
"""
host, port = host_port.split(':')
return jsonrpc.ServerProxy(
jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(host, int(port))))
def from_server(cls, host_port, timeout=60):
"""Return a proxy LM object with bound methods to support ngram
scoring.
"""
if host_port is None:
return None
host, port = host_port.split(':')
return jsonrpc.ServerProxy(jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(host, int(port)),
timeout=timeout))
def from_server(cls, host_port, timeout=60):
"""Return a proxy DependencyModel object with bound methods to
support retrieval of dependency probabiities.
"""
if host_port is None:
return None
host, port = host_port.split(':')
return jsonrpc.ServerProxy(
jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(host, int(port)), timeout=timeout))
def train_slave(self,
instances,
host,
port,
slaves=(),
minibatch_size=1,
timeout=None,
limit=65536,
**kwargs):
"""Run the slave process of a round-robin distributed learner. This
stores all the instances and model parameters (including large
initialized models) as object members and must therefore NEVER
be saved to disk.
"""
# Note the inversion here compared to the other methods. Slave models
# will never be saved to disk and need to store all their state,
# including runtime parameters, as class members.
self.params.update(kwargs)
self.params['timeout'] = timeout
self.instances = instances
if minibatch_size == 1:
self.machine_init_serial(instances, slaves=slaves, **self.params)
else:
self.machine_init_minibatch(instances,
minibatch_size=minibatch_size,
slaves=slaves,
**self.params)
srv_timeout = 3 * timeout if timeout is not None else 1000
server = jsonrpc.Server(
jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(host, int(port)),
limit=limit,
timeout=srv_timeout))
server.register_function(self.slave_init_weights)
server.register_function(self.slave_receive_weights)
server.register_function(self.slave_decode_instance)
server.register_function(self.slave_fetch_weight_update)
print "Serving at %s:%s with timeout %ds" % (host, port, srv_timeout)
server.serve()
parser = argparse.ArgumentParser(
description='Start an LM server')
parser.add_argument('--ngram_order', action='store', type=int,
help="order of n-grams to serve",
default=3)
parser.add_argument('--lm_path', action='store',
help="path to the trained SRILM language model",
default='/path/to/project/resources/LMs/sample.lm')
parser.add_argument('--host', action='store',
help="host to serve on (default localhost; 0.0.0.0 for public)",
default=socket.gethostname()) #os.environ['HOSTNAME']
parser.add_argument('--port', action='store', type=int,
help="port to serve on (default 8081)",
default=8081)
parser.add_argument('--timeout', action='store', type=int,
help="time limit for responses",
default=200)
args = parser.parse_args()
server = jsonrpc.Server(jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(args.host,
args.port),
timeout=args.timeout))
lm = LangModel(args.ngram_order, lm_path=args.lm_path)
server.register_function(lm.score_ngram)
server.register_function(lm.score_ngrams)
server.register_function(lm.score_sent)
print 'Serving %s-grams from %s on http://%s:%s' % (args.ngram_order,
args.lm_path, args.host, args.port)
server.serve()
action='store',
help="path to the WSJ in Stanford parse format",
default='/proj/fluke/users/kapil/resources/' +
'treebank-depenified-stanford/wsj_gold_stanford_all.deps')
parser.add_argument(
'--host',
action='store',
help="host to serve on (default localhost; 0.0.0.0 for public)",
default=os.environ['HOSTNAME'])
parser.add_argument('--port',
action='store',
type=int,
help="port to serve on (default 8082)",
default=8082)
parser.add_argument('--timeout',
action='store',
type=int,
help="time limit for responses",
default=60)
args = parser.parse_args()
server = jsonrpc.Server(
jsonrpc.JsonRpc20(),
jsonrpc.TransportTcpIp(addr=(args.host, args.port),
timeout=args.timeout))
dm = DependencyModel(args.treebank_path)
server.register_function(dm.get_logprob)
print 'Serving dependencies from %s on http://%s:%s' % \
(args.treebank_path, args.host, args.port)
server.serve()