print "Looking for Previous Model to load."
ModelName = Name
if ECAL and HCAL:
ModelName += "_Merged"
MyModel = ModelWrapper(Name=ModelName,
LoadPrevious=True,
OutputBase=OutputBase)
# You can load a previous model using "-L" option with the model directory.
if LoadModel and BuildModel:
print "Loading Model From:", LoadModel
if LoadModel[-1] == "/": LoadModel = LoadModel[:-1]
MyModel = ModelWrapper(Name=os.path.basename(LoadModel),
InDir=os.path.dirname(LoadModel),
OutputBase=OutputBase)
MyModel.Load(LoadModel)
if BuildModel and not MyModel.Model:
FailedLoad = True
else:
FailedLoad = False
# Or Build the model from scratch
if BuildModel and not MyModel.Model:
import keras
print "Building Model...",
if ECAL:
ECALModel = Convolutional3D(Name + "ECAL")
ECALModel.Build()
MyModel = ECALModel
# You can automatically load the latest previous training of this model.
if TestDefaultParam("LoadPreviousModel") and not LoadModel:
print "Looking for Previous Model to load."
ReconstructionModel = ModelWrapper(Name=Name,
LoadPrevious=True,
OutputBase=OutputBase)
# You can load a previous model using "-L" option with the model directory.
if LoadModel:
print "Loading Model From:", LoadModel
if LoadModel[-1] == "/": LoadModel = LoadModel[:-1]
ReconstructionModel = ModelWrapper(Name=os.path.basename(LoadModel),
InDir=os.path.dirname(LoadModel),
OutputBase=OutputBase)
ReconstructionModel.Load(LoadModel)
if not ReconstructionModel.Model:
FailedLoad = True
else:
FailedLoad = False
# Or Build the model from scratch
if FailedLoad:
import keras
print "Building Model...",
ReconstructionModel = Model2DViewsTo3D(
Name,
View1,
View2,