def check_server(self, profile):
try:
session = SSHSession(profile)
session.close()
return True
except:
return False
def __init__(self,
remote_profile,
context_type='local',
batch_type='slurm'):
self.remote_profile = remote_profile
if context_type == 'local':
self.session = LocalSession(remote_profile)
self.context = LocalContext
self.uuid_names = False
elif context_type == 'lazy-local':
self.session = None
self.context = LazyLocalContext
self.uuid_names = True
elif context_type == 'ssh':
self.session = SSHSession(remote_profile)
self.context = SSHContext
self.uuid_names = False
else:
raise RuntimeError('unknown context')
if batch_type == 'slurm':
self.batch = Slurm
elif batch_type == 'lsf':
self.batch = LSF
elif batch_type == 'pbs':
self.batch = PBS
elif batch_type == 'shell':
self.batch = Shell
elif batch_type == 'aws':
self.batch = AWS
else:
raise RuntimeError('unknown batch ' + batch_type)
def decide_model_devi_machine(mdata):
if 'model_devi' in mdata:
continue_flag = False
if 'record.machine' in os.listdir():
try:
with open('record.machine', 'r') as _infile:
profile = json.load(_infile)
if profile['purpose'] == 'model_devi':
mdata['model_devi_machine'] = profile['machine']
mdata['model_devi_resources'] = profile['resources']
mdata['lmp_command'] = profile['command']
mdata['model_devi_group_size'] = profile['group_size']
continue_flag = True
except:
pass
if "hostname" not in mdata["model_devi"][0]["machine"]:
mdata["model_devi_machine"] = mdata["model_devi"][0]["machine"]
mdata["model_devi_resources"] = mdata["model_devi"][0]["resources"]
mdata["lmp_command"] = mdata["model_devi"][0]["command"]
#if "group_size" in mdata["train"][0]:
mdata["model_devi_group_size"] = mdata["model_devi"][0][
"group_size"]
continue_flag = True
pd_count_list = []
pd_flag = False
if not continue_flag:
#assert isinstance(mdata['model_devi']['machine'], list)
#ssert isinstance(mdata['model_devi']['resources'], list)
#assert len(mdata['model_devi']['machine']) == len(mdata['model_devi']['resources'])
for machine_idx in range(len(mdata['model_devi'])):
temp_machine = mdata['model_devi'][machine_idx]['machine']
temp_resources = mdata['model_devi'][machine_idx]['resources']
#assert isinstance(temp_machine, dict), "unsupported type of model_devi machine [%d]!" %machine_idx
#assert isinstance(temp_resources, dict), "unsupported type of model_devi resources [%d]!"%machine_idx
#assert temp_machine['machine_type'] == 'slurm', "Currently only support for Slurm!"
temp_ssh_sess = SSHSession(temp_machine)
cwd = os.getcwd()
temp_context = SSHContext(cwd, temp_ssh_sess)
temp_batch = Slurm(temp_context)
command = temp_batch._make_squeue(temp_machine, temp_resources)
ret, stdin, stdout, stderr = temp_batch.context.block_call(
command)
pd_response = stdout.read().decode('utf-8').split("\n")
pd_count = len(pd_response)
temp_context.clean()
if pd_count == 0:
mdata['model_devi_machine'] = temp_machine
mdata['model_devi_resources'] = temp_resources
mdata['lmp_command'] = mdata['model_devi'][machine_idx][
'command']
mdata['model_devi_group_size'] = mdata['model_devi'][
machine_idx]['group_size']
pd_flag = True
break
else:
pd_count_list.append(pd_count)
if not pd_flag:
min_machine_idx = np.argsort(pd_count_list)[0]
mdata['model_devi_machine'] = mdata['model_devi'][
min_machine_idx]['machine']
mdata['model_devi_resources'] = mdata['model_devi'][
min_machine_idx]['resources']
mdata['lmp_command'] = mdata['model_devi'][min_machine_idx][
'command']
mdata['model_devi_group_size'] = mdata['model_devi'][
min_machine_idx]['group_size']
with open("record.machine", "w") as _outfile:
profile = {}
profile['purpose'] = 'model_devi'
profile['machine'] = mdata['model_devi_machine']
profile['resources'] = mdata['model_devi_resources']
profile['group_size'] = mdata['model_devi_group_size']
profile['command'] = mdata['lmp_command']
json.dump(profile, _outfile, indent=4)
return mdata
def decide_fp_machine(mdata):
if 'fp' in mdata:
#ssert isinstance(mdata['fp']['machine'], list)
#assert isinstance(mdata['fp']['resources'], list)
#assert len(mdata['fp']['machine']) == len(mdata['fp']['resources'])
continue_flag = False
## decide whether to use an existing machine
if 'record.machine' in os.listdir():
try:
with open('record.machine', 'r') as _infile:
profile = json.load(_infile)
if profile['purpose'] == 'fp':
mdata['fp_machine'] = profile['machine']
mdata['fp_resources'] = profile['resources']
mdata['fp_command'] = profile['command']
mdata['fp_group_size'] = profile['group_size']
#mdata['deepmd_path'] = profile['deepmd_path']
continue_flag = True
except:
pass
if "hostname" not in mdata["fp"][0]["machine"]:
mdata["fp_machine"] = mdata["fp"][0]["machine"]
mdata["fp_resources"] = mdata["fp"][0]["resources"]
mdata["fp_command"] = mdata["fp"][0]["command"]
#if "group_size" in mdata["train"][0]:
mdata["fp_group_size"] = mdata["fp"][0]["group_size"]
continue_flag = True
pd_count_list = []
pd_flag = False
if not continue_flag:
for machine_idx in range(len(mdata['fp'])):
temp_machine = mdata['fp'][machine_idx]['machine']
temp_resources = mdata['fp'][machine_idx]['resources']
temp_ssh_sess = SSHSession(temp_machine)
cwd = os.getcwd()
temp_context = SSHContext(cwd, temp_ssh_sess)
temp_batch = Slurm(temp_context)
command = temp_batch._make_squeue(temp_machine, temp_resources)
ret, stdin, stdout, stderr = temp_batch.context.block_call(
command)
pd_response = stdout.read().decode('utf-8').split("\n")
pd_count = len(pd_response)
temp_context.clean()
#dlog.info(temp_machine["username"] + " " + temp_machine["hostname"] + " " + str(pd_count))
if pd_count == 0:
mdata['fp_machine'] = temp_machine
mdata['fp_resources'] = temp_resources
mdata['fp_command'] = mdata['fp'][machine_idx]['command']
mdata['fp_group_size'] = mdata['fp'][machine_idx][
'group_size']
pd_flag = True
break
else:
pd_count_list.append(pd_count)
if not pd_flag:
min_machine_idx = np.argsort(pd_count_list)[0]
mdata['fp_machine'] = mdata['fp'][min_machine_idx]['machine']
mdata['fp_resources'] = mdata['fp'][min_machine_idx][
'resources']
mdata['fp_command'] = mdata['fp'][min_machine_idx]['command']
mdata['fp_group_size'] = mdata['fp'][min_machine_idx][
'group_size']
with open("record.machine", "w") as _outfile:
profile = {}
profile['purpose'] = 'fp'
profile['machine'] = mdata['fp_machine']
profile['resources'] = mdata['fp_resources']
profile['group_size'] = mdata['fp_group_size']
profile['command'] = mdata['fp_command']
json.dump(profile, _outfile, indent=4)
# print("mdata", mdata)
return mdata
def decide_train_machine(mdata):
if 'train' in mdata:
continue_flag = False
## decide whether to use an existing machine
if 'record.machine' in os.listdir():
try:
with open('record.machine', 'r') as _infile:
profile = json.load(_infile)
if profile['purpose'] == 'train':
mdata['train_machine'] = profile['machine']
mdata['train_resources'] = profile['resources']
mdata['deepmd_path'] = profile['deepmd_path']
if "group_size" in profile:
mdata["train_group_size"] = profile["group_size"]
continue_flag = True
except:
pass
if "hostname" not in mdata["train"][0]["machine"]:
mdata["train_machine"] = mdata["train"][0]["machine"]
mdata["train_resources"] = mdata["train"][0]["resources"]
mdata["deepmd_path"] = mdata["train"][0]["deepmd_path"]
if "group_size" in mdata["train"][0]:
mdata["train_group_size"] = mdata["train"][0]["group_size"]
continue_flag = True
pd_flag = False
pd_count_list = []
# pd for pending job in slurm
# if we need to launch new machine_idxines
if not continue_flag:
#assert isinstance(mdata['train']['machine'], list)
#assert isinstance(mdata['train']['resources'], list)
#assert len(mdata['train']['machine']) == len(mdata['train']['resources'])
# mdata['train'] is a list
for machine_idx in range(len(mdata['train'])):
temp_machine = mdata['train'][machine_idx]['machine']
temp_resources = mdata['train'][machine_idx]['resources']
temp_ssh_sess = SSHSession(temp_machine)
cwd = os.getcwd()
temp_context = SSHContext(cwd, temp_ssh_sess)
temp_batch = Slurm(temp_context)
command = temp_batch._make_squeue(temp_machine, temp_resources)
ret, stdin, stdout, stderr = temp_batch.context.block_call(
command)
pd_response = stdout.read().decode('utf-8').split("\n")
pd_count = len(pd_response)
temp_context.clean()
## If there is no need to waiting for allocation
if pd_count == 1:
mdata['train_machine'] = temp_machine
mdata['train_resources'] = temp_resources
mdata['deepmd_path'] = mdata['train'][machine_idx][
'deepmd_path']
## No need to wait
pd_flag = True
break
else:
pd_count_list.append(pd_count)
if not pd_flag:
## All machines need waiting, then compare waiting jobs
## Select a machine which has fewest waiting jobs
min_machine_idx = np.argsort(pd_count_list)[0]
mdata['train_machine'] = mdata['train'][min_machine_idx][
'machine']
mdata['train_resources'] = mdata['train'][min_machine_idx][
'resources']
mdata['deepmd_path'] = mdata['train'][min_machine_idx][
'deepmd_path']
if "group_size" in mdata['train'][min_machine_idx]:
mdata["train_group_size"] = mdata['train'][
min_machine_idx]["group_size"]
## Record which machine is selected
with open("record.machine", "w") as _outfile:
profile = {}
profile['purpose'] = 'train'
profile['machine'] = mdata['train_machine']
profile['resources'] = mdata['train_resources']
profile['deepmd_path'] = mdata['deepmd_path']
if "train_group_size" in mdata:
profile["group_size"] = mdata["train_group_size"]
json.dump(profile, _outfile, indent=4)
return mdata
def decide_fp_machine(mdata):
if LooseVersion(mdata.get('api_version', '0.9')) >= LooseVersion('1.0'):
mdata['fp_group_size'] = mdata['fp'][0]['resources']['group_size']
if 'fp' in mdata:
#ssert isinstance(mdata['fp']['machine'], list)
#assert isinstance(mdata['fp']['resources'], list)
#assert len(mdata['fp']['machine']) == len(mdata['fp']['resources'])
continue_flag = False
## decide whether to use an existing machine
if 'record.machine' in os.listdir():
try:
with open('record.machine', 'r') as _infile:
profile = json.load(_infile)
if profile['purpose'] == 'fp':
mdata['fp_machine'] = profile['machine']
mdata['fp_resources'] = profile['resources']
mdata['fp_command'] = profile['command']
mdata['fp_group_size'] = profile['group_size']
continue_flag = True
except:
pass
if ("hostname" not in mdata["fp"][0]["machine"]) or (len(mdata["fp"])
== 1):
mdata["fp_machine"] = mdata["fp"][0]["machine"]
mdata["fp_resources"] = mdata["fp"][0]["resources"]
mdata["fp_command"] = mdata["fp"][0]["command"]
#if "group_size" in mdata["train"][0]:
mdata["fp_group_size"] = mdata["fp"][0].get("group_size", 1)
continue_flag = True
pd_count_list = []
pd_flag = False
if not continue_flag:
for machine_idx in range(len(mdata['fp'])):
temp_machine = mdata['fp'][machine_idx]['machine']
temp_resources = mdata['fp'][machine_idx]['resources']
temp_ssh_sess = SSHSession(temp_machine)
cwd = os.getcwd()
temp_context = SSHContext(cwd, temp_ssh_sess)
if temp_machine['machine_type'] == 'lsf':
temp_batch = LSF(temp_context)
else:
temp_batch = Slurm(temp_context)
# For other type of machines, please add them using 'elif'.
# Here slurm is selected as the final choice in convinience.
command = temp_batch._make_squeue(temp_machine, temp_resources)
ret, stdin, stdout, stderr = temp_batch.context.block_call(
command)
pd_response = stdout.read().decode('utf-8').split("\n")
pd_count = len(pd_response)
temp_context.clean()
#dlog.info(temp_machine["username"] + " " + temp_machine["hostname"] + " " + str(pd_count))
if pd_count == 0:
mdata['fp_machine'] = temp_machine
mdata['fp_resources'] = temp_resources
mdata['fp_command'] = mdata['fp'][machine_idx]['command']
mdata['fp_group_size'] = mdata['fp'][machine_idx].get(
'group_size', 1)
pd_flag = True
break
else:
pd_count_list.append(pd_count)
if not pd_flag:
min_machine_idx = np.argsort(pd_count_list)[0]
mdata['fp_machine'] = mdata['fp'][min_machine_idx]['machine']
mdata['fp_resources'] = mdata['fp'][min_machine_idx][
'resources']
mdata['fp_command'] = mdata['fp'][min_machine_idx]['command']
mdata['fp_group_size'] = mdata['fp'][min_machine_idx].get(
'group_size', 1)
with open("record.machine", "w") as _outfile:
profile = {}
profile['purpose'] = 'fp'
profile['machine'] = mdata['fp_machine']
profile['resources'] = mdata['fp_resources']
profile['group_size'] = mdata['fp_group_size']
profile['command'] = mdata['fp_command']
json.dump(profile, _outfile, indent=4)
return mdata
