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: