if Train or (RecoverMode and FailedLoad):
print "Training."
# Setup Callbacks
# These are all optional.
from DLTools.CallBacks import TimeStopping, GracefulExit
from keras.callbacks import *
callbacks = []
# Still testing this...
if TestDefaultParam("UseGracefulExit", 0):
print "Adding GracefulExit Callback."
callbacks.append(GracefulExit())
if TestDefaultParam("ModelCheckpoint", False):
MyModel.MakeOutputDir()
callbacks.append(
ModelCheckpoint(MyModel.OutDir + "/Checkpoint.Weights.h5",
monitor=TestDefaultParam("monitor", "val_loss"),
save_best_only=TestDefaultParam(
"ModelCheckpoint_save_best_only"),
save_weights_only=TestDefaultParam(
"ModelCheckpoint_save_weights_only"),
mode=TestDefaultParam("ModelCheckpoint_mode",
"auto"),
period=TestDefaultParam("ModelCheckpoint_period",
1),
verbose=0))
if TestDefaultParam("EarlyStopping"):
callbacks.append(
if Train or (RecoverMode and FailedLoad):
print "Training."
# Setup Callbacks
# These are all optional.
from DLTools.CallBacks import TimeStopping, GracefulExit
from keras.callbacks import *
callbacks = []
# Still testing this...
if TestDefaultParam("UseGracefulExit", 0):
print "Adding GracefulExit Callback."
callbacks.append(GracefulExit())
if TestDefaultParam("ModelCheckpoint", False):
ReconstructionModel.MakeOutputDir()
callbacks.append(
ModelCheckpoint(
ReconstructionModel.OutDir + "/Checkpoint.Weights.h5",
monitor=TestDefaultParam("monitor", "val_loss"),
save_best_only=TestDefaultParam(
"ModelCheckpoint_save_best_only"),
save_weights_only=TestDefaultParam(
"ModelCheckpoint_save_weights_only"),
mode=TestDefaultParam("ModelCheckpoint_mode", "auto"),
period=TestDefaultParam("ModelCheckpoint_period", 1),
verbose=0))
if TestDefaultParam("EarlyStopping"):
callbacks.append(
keras.callbacks.EarlyStopping(