def save_model_weights(): encoder .save_weights( "models/encoder.h5" ) decoder_A.save_weights( "models/decoder_A.h5" ) decoder_B.save_weights( "models/decoder_B.h5" ) print( "\nSave model weights" )
def save_model_weights(): encoder .save_weights( "/input/data/models/encoder.h5" ) decoder_A.save_weights( "/input/data/models/decoder_A.h5" ) decoder_B.save_weights( "/input/data/models/decoder_B.h5" ) print( "save model weights" )
def save_model_weights(mdl): encoder.save_weights(mdl + "/encoder.h5") decoder_A.save_weights(mdl + "/decoder_A.h5") decoder_B.save_weights(mdl + "/decoder_B.h5") print("Savign model weights")
def save_model_weights(): encoder .save_weights(modelpath + "models/encoder.h5" ) decoder_A.save_weights(modelpath + "models/decoder_A.h5" ) decoder_B.save_weights(modelpath + "models/decoder_B.h5" ) print( "save model weights" )
def save_model_weights(): encoder .save_weights( "models/encoder.h5" ) decoder_A.save_weights( "models/decoder_A.h5" ) decoder_B.save_weights( "models/decoder_B.h5" ) print( "save model weights" )