def trainEval(param):
pconf = conf(param)
#print("======= CREATE MODEL")
model, optim = fun.makeModel(pconf, device)
#print("======= LOAD DATA")
dataloaders, _ = fun.processData(pconf)
#print("======= TRAIN MODEL")
fun.runTrain(pconf, model, optim, dataloaders, tuneLog=True)
def myRun(conf, k, lock):
valid = False
while not valid:
valid = True
lock.acquire()
try:
print("======= CREATE MODEL {}".format(k))
model, optim = fun.makeModel(conf[k], device)
print("======= LOAD DATA {}".format(k))
dataloaders, _ = fun.processData(conf[k])
print("======= TRAIN MODEL {}".format(k))
except RuntimeError as e:
print("======= RETRY MODEL {}".format(k))
valid = False
lock.release()
if valid:
fun.runTrain(conf[k], model, optim, dataloaders)
lock.acquire()
print("======= FINISH MODEL {}".format(k))
lock.release()
else:
time.sleep(120)
#import os
#os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID";
#os.environ["CUDA_VISIBLE_DEVICES"]="0";
import configurationsPrimeTest as configurations
import funPytorch as fun
conf = configurations.configRun1
device = "cuda:0"
#model.main(configurations.configRun1)
print("======= CREATE MODEL")
model, optim = fun.makeModel(conf, device)
print("======= LOAD DATA")
X, y, train, valid, test = fun.processData(conf)
print("======= TRAIN MODEL")
fun.runTrain(conf, model, optim, X, y, train, valid, test)
#print("======= TEST MODEL")
#fun.runTest(conf, model, X, y, test)
#print("======= SAVE MODEL")
#fun.saveModel(conf, model, optim)
