def Dump(model,fnameMODEL,fnameWeight):
if str(type(model)).find("sklearn.")==-1:
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
json_string = model.to_json()
fm = open(fnameMODEL+".json","w")
fm.write(json_string)
fm.close()
model.save_weights(fnameWeight+".hdf5",overwrite=True)
else:
from sklearn.externals import joblib
def ensure_dir(f):
d = os.path.dirname(f)
if not os.path.exists(d):
os.makedirs(d)
ensure_dir('./skmodel/')
joblib.dump(model, "./skmodel/"+fnameMODEL+".pkl",compress=3)
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