print(fitness)
        return fitness
    except Exception as e:
        print("error in evaluation")
        print(e)
        return [[-1],[-1]]




# CONFIG
try: theano.config.device = 'gpu'
except: pass
theano.config.floatX = 'float32'
numpy.random.seed(0)
training_data, validation_data, test_data = load_data(data_split=params["data_split"])

fns = {
    "generate": generate,
    "evaluate": evaluate,
    "evaluateBest": evaluateBest,
    "mutate": mutate,
    "crossover": crossover,
    "getFitness": getFitness
}
dump_file = "dump.obj"
if len(sys.argv) > 1:
    if sys.argv[1] == "resume" and len(sys.argv) == 3:
        dump_file = sys.argv[2]

ga = GAlg(ga_params, fns, dump_file)
    #         if ind["fitness"] is not None:
    #             print(ind["fitness"][1][-1]),
    #     print("")
    # print(len(generations))
    # # print(len(generations))
    # # for generation in generations:
    # #     print(len(generation))



# CONFIG
# try: theano.config.device = 'gpu'
# except: pass
theano.config.floatX = 'float32'
numpy.random.seed(0)
training_data, validation_data, test_data = load_data()

fns = {
    "generate": generate,
    "evaluate": evaluate,
    "evaluateBest": evaluateBest,
    "mutate": mutate,
    "crossover": crossover,
    "getFitness": getFitness,
    "processData": processData
}
dump_file = "dump.obj"
if len(sys.argv) > 1:
    if sys.argv[1] == "resume" and len(sys.argv) == 3:
        dump_file = sys.argv[2]
    elif len(sys.argv) == 2: