def json_input(self, args):
if (self.uobject.VerbosePythonLog):
ue.log(self.uobject.TensorFlowModule + ' input passed: ' + args)
#branch based on threading
if (self.uobject.ShouldUseMultithreading):
ut.run_on_bt(self.json_input_blocking, args)
else:
self.json_input_blocking(args)
def setup(self, args=None):
if (self.uobject.ShouldUseMultithreading):
try:
if (self.uobject.VerbosePythonLog):
ue.log('running setup on background thread')
ut.run_on_bt(self.setup_blocking)
except:
e = sys.exc_info()[0]
ue.log('TensorFlowComponent::setup error: ' + str(e))
else:
self.setup_blocking()
def train(self, args=None):
if (self.uobject.VerbosePythonLog):
ue.log(self.uobject.TensorFlowModule + ' training scheduled.')
if (self.uobject.ShouldUseMultithreading):
try:
ut.run_on_bt(self.trainBlocking)
except:
e = sys.exc_info()[0]
ue.log('TensorFlowComponent error: ' + str(e))
else:
self.trainBlocking()
def train(self, args=None):
if(self.uobject.VerbosePythonLog):
ue.log(self.uobject.TensorFlowModule + ' training scheduled.')
if(self.uobject.ShouldUseMultithreading):
try:
ut.run_on_bt(self.trainBlocking)
except:
e = sys.exc_info()[0]
ue.log('TensorFlowComponent error: ' + str(e))
else:
self.trainBlocking()
def train(self, args=None):
#ensure our training trigger is reset
self.tfapi._resetTrainingTrigger()
if (self.uobject.VerbosePythonLog):
ue.log(self.uobject.TensorFlowModule + ' training scheduled.')
if (self.uobject.ShouldUseMultithreading):
try:
ut.run_on_bt(self.train_blocking)
except:
e = sys.exc_info()[0]
ue.log('TensorFlowComponent::train error: ' + str(e))
else:
self.train_blocking()
def test():
#Train()
ut.run_on_bt(Train)
def testp():
ut.run_on_bt(doLongTask)
def test3():
ut.run_on_bt(yolo, yolodone)
def test2():
ut.run_on_bt(yolo)
def test(): #Train() ut.run_on_bt(Train)
