def _start_tf_cluster(self):
cluster_def = {}
tasks = sorted(self.tasks.values(), key=lambda task: task.task_index)
for task in tasks:
cluster_def.setdefault(task.job_name, []).append(task.addr)
for id, task in iteritems(self.tasks):
response = {
'job_name': task.job_name,
'task_index': task.task_index,
'cpus': task.cpus,
'mem': task.mem,
'gpus': task.gpus,
'cmd': task.cmd,
'cwd': os.getcwd(),
'cluster_def': cluster_def,
'forward_addresses': self.forward_addresses,
'extra_config': self.extra_config,
'protocol': self.protocol
}
send(task.connection, response)
assert recv(task.connection) == 'ok'
logger.info('Device /job:%s/task:%s activated @ grpc://%s ',
task.job_name, task.task_index, task.addr)
task.connection.close()
def _start_tf_cluster(self):
cluster_def = {}
tasks = sorted(self.tasks.values(), key=lambda task: task.task_index)
for task in tasks:
cluster_def.setdefault(task.job_name, []).append(task.addr)
for id, task in iteritems(self.tasks):
response = {
'job_name': task.job_name,
'task_index': task.task_index,
'cpus': task.cpus,
'mem': task.mem,
'gpus': task.gpus,
'cmd': task.cmd,
'cwd': os.getcwd(),
'cluster_def': cluster_def,
'forward_addresses': self.forward_addresses,
'extra_config': self.extra_config,
'protocol': self.protocol
}
send(task.connection, response)
assert recv(task.connection) == 'ok'
logger.info(
'Device /job:%s/task:%s activated @ grpc://%s ',
task.job_name,
task.task_index,
task.addr
)
task.connection.close()
def _start_tf_cluster(self):
cluster_def = {}
targets = {}
for task in self.tasks:
target_name = '/job:%s/task:%s' % (task.job_name, task.task_index)
grpc_addr = 'grpc://%s' % task.addr
targets[target_name] = grpc_addr
cluster_def.setdefault(task.job_name, []).append(task.addr)
if self.local_task:
job_name, addr = self.local_task
cluster_def.setdefault(job_name, []).insert(0, addr)
for task in self.tasks:
response = {
'job_name': task.job_name,
'task_index': task.task_index,
'cpus': task.cpus,
'mem': task.mem,
'gpus': task.gpus,
'cmd': task.cmd,
'cwd': os.getcwd(),
'cluster_def': cluster_def,
}
send(task.connection, response)
assert recv(task.connection) == 'ok'
logger.info('Device /job:%s/task:%s activated @ grpc://%s ',
task.job_name, task.task_index, task.addr)
task.connection.close()
return targets
def main(argv):
mesos_task_id, maddr = argv[1:]
mesos_task_id = int(mesos_task_id)
maddr = maddr.split(':', 2)
maddr = (maddr[0], int(maddr[1]))
lfd = socket.socket()
lfd.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
lfd.bind(('', 0))
addr = "%s:%s" % (socket.gethostname(), lfd.getsockname()[1])
job_name = None
task_index = None
mem = None
cpus = None
c = socket.socket()
c.connect(maddr)
send(c, (mesos_task_id, addr))
response = recv(c)
cluster_def = response["cluster_def"]
job_name = response["job_name"]
task_index = response["task_index"]
cpus = response["cpus"]
mem = response["mem"]
gpus = response["gpus"]
cmd = response["cmd"]
cwd = response["cwd"]
send(c, 'ok')
c.close()
if cmd is None:
server_def = tf.train.ServerDef(
cluster=tf.train.ClusterSpec(cluster_def).as_cluster_def(),
job_name=job_name,
task_index=task_index,
protocol="grpc",
)
server_def.default_session_config.device_count["CPU"] = int(cpus)
server_def.default_session_config.device_count["GPU"] = int(gpus)
(soft, hard) = resource.getrlimit(resource.RLIMIT_AS)
soft = min(float(mem), soft, hard)
resource.setrlimit(resource.RLIMIT_AS, (soft, hard))
server = tf.train.Server(server_def)
try:
server.join()
except:
return
else:
server_name = 'ps'
worker_name = 'worker'
ps_hosts = ','.join(cluster_def[server_name])
worker_hosts = ','.join(cluster_def[worker_name])
cmd = cmd.format(ps_hosts=ps_hosts,
worker_hosts=worker_hosts,
job_name=job_name,
task_index=task_index)
subprocess.check_call(cmd, shell=True, cwd=cwd)
def _start_tf_cluster(self):
cluster_def = {}
targets = {}
for task in self.tasks:
target_name = '/job:%s/task:%s' % (task.job_name, task.task_index)
grpc_addr = 'grpc://%s' % task.addr
targets[target_name] = grpc_addr
cluster_def.setdefault(task.job_name, []).append(task.addr)
for task in self.tasks:
response = {
"job_name": task.job_name,
"task_index": task.task_index,
"cpus": task.cpus,
"mem": task.mem,
"cluster_def": cluster_def,
}
send(task.connection, response)
assert recv(task.connection) == "ok"
logger.info(
"Device /job:%s/task:%s activated @ grpc://%s " % (
task.job_name,
task.task_index,
task.addr
)
)
task.connection.close()
return targets
def main(argv):
mesos_task_id, maddr = argv[1:]
mesos_task_id = int(mesos_task_id)
maddr = maddr.split(':', 2)
maddr = (maddr[0], int(maddr[1]))
lfd = socket.socket()
lfd.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
lfd.bind(('', 0))
addr = "%s:%s" % (socket.gethostname(), lfd.getsockname()[1])
job_name = None
task_index = None
mem = None
cpus = None
c = socket.socket()
c.connect(maddr)
send(c, (mesos_task_id, addr))
response = recv(c)
cluster_def = response["cluster_def"]
job_name = response["job_name"]
task_index = response["task_index"]
cpus = response["cpus"]
mem = response["mem"]
server_def = tf.train.ServerDef(
cluster=tf.train.ClusterSpec(cluster_def).as_cluster_def(),
job_name=job_name,
task_index=task_index,
protocol="grpc",
)
server_def.default_session_config.device_count["CPU"] = int(cpus)
server_def.default_session_config.device_count["GPU"] = 0
(soft, hard) = resource.getrlimit(resource.RLIMIT_AS)
soft = min(float(mem), soft, hard)
resource.setrlimit(resource.RLIMIT_AS, (soft, hard))
server = tf.train.Server(server_def)
send(c, 'ok')
c.close()
try:
server.join()
except:
return
def _start_tf_cluster(self):
cluster_def = {}
targets = {}
for task in self.tasks:
target_name = '/job:%s/task:%s' % (task.job_name, task.task_index)
grpc_addr = 'grpc://%s' % task.addr
targets[target_name] = grpc_addr
cluster_def.setdefault(task.job_name, []).append(task.addr)
for task in self.tasks:
response = {
"job_name": task.job_name,
"task_index": task.task_index,
"cpus": task.cpus,
"mem": task.mem,
"cluster_def": cluster_def,
}
send(task.connection, response)
assert recv(task.connection) == "ok"
logger.info("Device /job:%s/task:%s activated @ grpc://%s " %
(task.job_name, task.task_index, task.addr))
task.connection.close()
return targets
def _start_tf_cluster(self):
cluster_def = {}
targets = {}
for task in self.tasks:
target_name = '/job:%s/task:%s' % (task.job_name, task.task_index)
grpc_addr = 'grpc://%s' % task.addr
targets[target_name] = grpc_addr
cluster_def.setdefault(task.job_name, []).append(task.addr)
if self.local_task:
job_name, addr = self.local_task
cluster_def.setdefault(job_name, []).insert(0, addr)
for task in self.tasks:
response = {
'job_name': task.job_name,
'task_index': task.task_index,
'cpus': task.cpus,
'mem': task.mem,
'gpus': task.gpus,
'cmd': task.cmd,
'cwd': os.getcwd(),
'cluster_def': cluster_def,
}
send(task.connection, response)
assert recv(task.connection) == 'ok'
logger.info(
'Device /job:%s/task:%s activated @ grpc://%s ',
task.job_name,
task.task_index,
task.addr
)
task.connection.close()
return targets
def main(argv):
mesos_task_id, maddr = argv[1:]
maddr = maddr.split(':', 2)
maddr = (maddr[0], int(maddr[1]))
lfd = socket.socket()
lfd.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
lfd.bind(('', 0))
addr = "%s:%s" % (socket.gethostname(), lfd.getsockname()[1])
job_name = None
task_index = None
cpus = None
c = socket.socket()
c.connect(maddr)
send(c, (mesos_task_id, addr))
response = recv(c)
cluster_def = response["cluster_def"]
job_name = response["job_name"]
task_index = response["task_index"]
cpus = response["cpus"]
gpus = response["gpus"]
cmd = response["cmd"]
cwd = response["cwd"]
extra_config = response['extra_config']
forward_addresses = response['forward_addresses']
protocol = response['protocol']
forward_fd = None
grpc_addr = '/job:%s/task:%s' % (job_name, task_index)
if forward_addresses and grpc_addr in forward_addresses:
addr = forward_addresses[grpc_addr]
forward_fd = socket.socket()
forward_fd.connect(addr)
send(c, 'ok')
c.close()
if cmd is None:
server_def = tf.train.ServerDef(
cluster=tf.train.ClusterSpec(cluster_def).as_cluster_def(),
job_name=job_name,
task_index=task_index,
protocol=protocol,
)
server_def.default_session_config.device_count["CPU"] = int(cpus)
server_def.default_session_config.device_count["GPU"] = int(gpus)
server = tf.train.Server(server_def)
try:
server.join()
except:
return
else:
initial_cmd = extra_config.get('initializer')
if initial_cmd is not None:
subprocess.check_call(initial_cmd, shell=True)
server_name = 'ps'
worker_name = 'worker'
ps_hosts = ','.join(cluster_def[server_name])
worker_hosts = ','.join(cluster_def[worker_name])
cmd = cmd.format(ps_hosts=ps_hosts,
worker_hosts=worker_hosts,
job_name=job_name,
task_index=task_index)
try:
subprocess.check_call(cmd, shell=True, cwd=cwd, stdout=forward_fd)
finally:
final_cmd = extra_config.get('finalizer')
if final_cmd is not None:
logger.info('Running clean up command {}'.format(final_cmd))
subprocess.check_call(final_cmd, shell=True)
if forward_fd:
forward_fd.close()
def main(argv):
mesos_task_id, maddr = argv[1:]
maddr = maddr.split(':', 2)
maddr = (maddr[0], int(maddr[1]))
lfd = socket.socket()
lfd.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
lfd.bind(('', 0))
addr = "%s:%s" % (socket.gethostname(), lfd.getsockname()[1])
job_name = None
task_index = None
cpus = None
c = socket.socket()
c.connect(maddr)
send(c, (mesos_task_id, addr))
response = recv(c)
cluster_def = response["cluster_def"]
job_name = response["job_name"]
task_index = response["task_index"]
cpus = response["cpus"]
gpus = response["gpus"]
cmd = response["cmd"]
cwd = response["cwd"]
extra_config = response['extra_config']
forward_addresses = response['forward_addresses']
protocol = response['protocol']
forward_fd = None
grpc_addr = '/job:%s/task:%s' % (job_name, task_index)
if forward_addresses and grpc_addr in forward_addresses:
addr = forward_addresses[grpc_addr]
forward_fd = socket.socket()
forward_fd.connect(addr)
send(c, 'ok')
c.close()
if cmd is None:
server_def = tf.train.ServerDef(
cluster=tf.train.ClusterSpec(cluster_def).as_cluster_def(),
job_name=job_name,
task_index=task_index,
protocol=protocol,
)
server_def.default_session_config.device_count["CPU"] = int(cpus)
server_def.default_session_config.device_count["GPU"] = int(gpus)
server = tf.train.Server(server_def)
try:
server.join()
except Exception:
return 0
else:
initial_cmd = extra_config.get('initializer')
if initial_cmd is not None:
subprocess.check_call(initial_cmd, shell=True)
server_name = 'ps'
worker_name = 'worker'
ps_hosts = ','.join(cluster_def[server_name])
worker_hosts = ','.join(cluster_def[worker_name])
env = os.environ.copy()
env['PYTHONUNBUFFERED'] = '1'
prefix = '[%s:%s] ' % (job_name, task_index)
prefix = prefix.encode('ascii')
cmd = cmd.format(ps_hosts=ps_hosts,
worker_hosts=worker_hosts,
job_name=job_name,
task_index=task_index)
out = os.fdopen(sys.stdout.fileno(), 'wb', 1)
try:
p = subprocess.Popen(cmd,
shell=True,
cwd=cwd,
stdout=subprocess.PIPE,
bufsize=1,
env=env)
for l in iter(p.stdout.readline, b''):
out.write(l)
if forward_fd:
forward_fd.send(prefix + l)
return p.wait()
finally:
final_cmd = extra_config.get('finalizer')
if final_cmd is not None:
logger.info('Running clean up command {}'.format(final_cmd))
subprocess.check_call(final_cmd, shell=True)
out.close()
if forward_fd:
forward_fd.close()
def main(argv):
mesos_task_id, maddr = argv[1:]
maddr = maddr.split(':', 2)
maddr = (maddr[0], int(maddr[1]))
lfd = socket.socket()
lfd.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
lfd.bind(('', 0))
addr = "%s:%s" % (socket.gethostname(), lfd.getsockname()[1])
job_name = None
task_index = None
cpus = None
c = socket.socket()
c.connect(maddr)
send(c, (mesos_task_id, addr))
response = recv(c)
cluster_def = response["cluster_def"]
job_name = response["job_name"]
task_index = response["task_index"]
cpus = response["cpus"]
gpus = response["gpus"]
cmd = response["cmd"]
cwd = response["cwd"]
extra_config = response['extra_config']
forward_addresses = response['forward_addresses']
protocol = response['protocol']
forward_fd = None
grpc_addr = '/job:%s/task:%s' % (job_name, task_index)
if forward_addresses and grpc_addr in forward_addresses:
addr = forward_addresses[grpc_addr]
forward_fd = socket.socket()
forward_fd.connect(addr)
send(c, 'ok')
c.close()
if cmd is None:
server_def = tf.train.ServerDef(
cluster=tf.train.ClusterSpec(cluster_def).as_cluster_def(),
job_name=job_name,
task_index=task_index,
protocol=protocol,
)
server_def.default_session_config.device_count["CPU"] = int(cpus)
server_def.default_session_config.device_count["GPU"] = int(gpus)
server = tf.train.Server(server_def)
try:
server.join()
except Exception:
return 0
else:
initial_cmd = extra_config.get('initializer')
if initial_cmd is not None:
subprocess.check_call(initial_cmd, shell=True)
server_name = 'ps'
worker_name = 'worker'
ps_hosts = ','.join(cluster_def[server_name])
worker_hosts = ','.join(cluster_def[worker_name])
env = os.environ.copy()
env.update({
'PYTHONUNBUFFERED': '1',
'TFMESOS_PS_HOSTS': ps_hosts,
'TFMESOS_WORKER_HOSTS': worker_hosts,
'TFMESOS_JOB_NAME': job_name,
'TFMESOS_TASK_INDEX': str(task_index),
'TFMESOS_DISTRIBUTED': '1'
})
prefix = '[%s:%s] ' % (job_name, task_index)
prefix = prefix.encode('ascii')
cmd = cmd.format(
ps_hosts=ps_hosts, worker_hosts=worker_hosts,
job_name=job_name, task_index=task_index
)
out = os.fdopen(sys.stdout.fileno(), 'wb', 1)
try:
p = subprocess.Popen(
cmd, shell=True, cwd=cwd, stdout=subprocess.PIPE,
bufsize=1, env=env
)
for l in iter(p.stdout.readline, b''):
out.write(l)
if forward_fd:
forward_fd.send(prefix + l)
return p.wait()
finally:
final_cmd = extra_config.get('finalizer')
if final_cmd is not None:
logger.info('Running clean up command {}'.format(final_cmd))
subprocess.check_call(final_cmd, shell=True)
out.close()
if forward_fd:
forward_fd.close()