def _init(port):
connection = Connection.Connection(ip='localhost', port=port, server=False)
status, data = connection.readMessage()
assert status == STATUS_INIT_MODEL
modelAsBytes, trainerSettings = data
modelAbsPath = _writeModelToDiskAsBytes(modelAsBytes)
Hyperparameters.REPLAY_BUFFER_LENGTH = trainerSettings[0]
Hyperparameters.SLIDING_WINDOW_TURNS_TO_FULL = trainerSettings[1]
# Used for naming the runtime analasys log
if ("Y" in input("Use old training data (Y/N):").upper()):
MemoryBuffers.loadOldTrainingDataFromDisk()
return connection, modelAbsPath
def benchmark():
import RootDir
print("Loading training data...")
MemoryBuffers.loadOldTrainingDataFromDisk()
absPath = RootDir.getAbsolutePath(input("ModelName: "))
gpuSettings = input("Gpu Settings: ")
t1 = time.time()
dStates, dEvals, dPolics = MemoryBuffers.getDistinctTrainingData()
print("Data pre-processing finished:", time.time() - t1)
useMultipleModels = MachineSpecificSettings.AMOUNT_OF_GPUS > 1
_fitModelProc(absPath, useMultipleModels, gpuSettings, 0, dStates, dEvals,
dPolics, t1)
print("Full training finished:", time.time() - t1)