def runCloud(self, data):
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = data["jobName"]
job.indata = json.dumps(data)
job.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
data["exec"] = "'bash'"
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
# data["cores"] = 4
data["options"] = ""
cmd = "exec/mcem2.r --steps {steps} --seed {seed} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
# cmd = "exec/mcem2.r --K.ce 1000 --K.em 100 --rho .01 --pcutoff .05"
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
job.put()
cloud_params = {
"job_id" : job.key().id(),
"job_type": "mcem2",
# "cores": data["cores"],
"paramstring": cmd,
"model_file": stringModel,
"model_data": {
"content": self.addWeightColumnIfNecessary(iFileData["data"]),
"extension": "txt"
},
"final_data": {
"content": self.addWeightColumnIfNecessary(jFileData["data"]),
"extension": "txt"
},
"key_prefix": self.user.user_id(),
"credentials": self.user_data.getCredentials(),
"bucketname": self.user_data.getBucketName()
}
# # execute cloud task
try:
service = backend.backendservice.backendservices(self.user_data)
cloud_result = service.submit_cloud_task(params=cloud_params)
if not cloud_result["success"]:
raise Exception(cloud_result["reason"])
job.cloudDatabaseID = cloud_result["db_id"]
job.resource = cloud_result['resource']
job.celeryPID = cloud_result["celery_pid"]
# job.pollProcessPID = int(cloud_result["poll_process_pid"])
# job.pid = handle.pid
job.put()
except Exception as e:
job.status='Failed'
job.delete(self)
raise
return job
def runCloud(self, data):
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = data["jobName"]
job.indata = json.dumps(data)
job.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
data["exec"] = "'bash'"
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
# data["cores"] = 4
data["options"] = ""
cmd = "exec/mcem2.r --steps {steps} --seed {seed} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
# cmd = "exec/mcem2.r --K.ce 1000 --K.em 100 --rho .01 --pcutoff .05"
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
job.put()
cloud_params = {
"job_id" : job.key().id(),
"job_type": "mcem2",
# "cores": data["cores"],
"paramstring": cmd,
"model_file": stringModel,
"model_data": {
"content": self.addWeightColumnIfNecessary(iFileData["data"]),
"extension": "txt"
},
"final_data": {
"content": self.addWeightColumnIfNecessary(jFileData["data"]),
"extension": "txt"
},
"key_prefix": self.user.user_id(),
"credentials": self.user_data.getCredentials(),
"bucketname": self.user_data.getBucketName()
}
# # execute cloud task
try:
service = backend.backendservice.backendservices(self.user_data)
cloud_result = service.submit_cloud_task(params=cloud_params)
if not cloud_result["success"]:
raise Exception(cloud_result["reason"])
job.cloudDatabaseID = cloud_result["db_id"]
job.resource = cloud_result['resource']
job.celeryPID = cloud_result["celery_pid"]
# job.pollProcessPID = int(cloud_result["poll_process_pid"])
# job.pid = handle.pid
job.put()
except Exception as e:
job.status='Failed'
job.delete(self)
raise
return job
def runLocal(self, data):
'''
'''
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = data["jobName"]
job.indata = json.dumps(data)
job.outData = dataDir
job.modelName = modelDb.name
job.resource = "local"
job.status = "Running"
# Convert model and write to file
model_file_file = tempfile.mktemp(prefix = 'modelFile', suffix = '.R', dir = dataDir)
mff = open(model_file_file, 'w')
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
mff.write(stringModel)
mff.close()
data["model_file_file"] = model_file_file
model_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
mdf = open(model_data_file, 'w')
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
mdf.write(self.addWeightColumnIfNecessary(jFileData["data"]))
mdf.close()
data["model_data_file"] = model_data_file
model_initial_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
midf = open(model_initial_data_file, 'w')
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
midf.write(self.addWeightColumnIfNecessary(iFileData["data"]))
midf.close()
data["model_initial_data_file"] = model_initial_data_file
data["exec"] = "\"bash&\""
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
try:
import multiprocessing
data["cores"] = multiprocessing.cpu_count()
except:
data["cores"] = 1
data["options"] = ""
data["path"] = path
cmd = "Rscript --vanilla {path}/../../stochoptim/exec/mcem2.r --model {model_file_file} --data {model_initial_data_file} --finalData {model_data_file} --steps {steps} --seed {seed} --cores {cores} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(basedir, dataDir, cmd)
handle = subprocess.Popen(exstring, shell=True, preexec_fn=os.setsid)
job.pid = handle.pid
job.put()
return job
def runLocal(self, data):
'''
'''
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = data["jobName"]
job.indata = json.dumps(data)
job.outData = dataDir
job.modelName = modelDb.name
job.resource = "local"
job.status = "Running"
# Convert model and write to file
model_file_file = tempfile.mktemp(prefix = 'modelFile', suffix = '.R', dir = dataDir)
mff = open(model_file_file, 'w')
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
mff.write(stringModel)
mff.close()
data["model_file_file"] = model_file_file
model_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
mdf = open(model_data_file, 'w')
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
mdf.write(self.addWeightColumnIfNecessary(jFileData["data"]))
mdf.close()
data["model_data_file"] = model_data_file
model_initial_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
midf = open(model_initial_data_file, 'w')
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
midf.write(self.addWeightColumnIfNecessary(iFileData["data"]))
midf.close()
data["model_initial_data_file"] = model_initial_data_file
data["exec"] = "\"bash&\""
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
try:
import multiprocessing
data["cores"] = multiprocessing.cpu_count()
except:
data["cores"] = 1
data["options"] = ""
data["path"] = path
cmd = "Rscript --vanilla {path}/../../stochoptim/exec/mcem2.r --model {model_file_file} --data {model_initial_data_file} --finalData {model_data_file} --steps {steps} --seed {seed} --cores {cores} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(basedir, dataDir, cmd)
handle = subprocess.Popen(exstring, shell=True, preexec_fn=os.setsid)
job.pid = handle.pid
job.put()
return job
