def save_model(model: Model,
path: str,
include_optimizer: bool = False,
meta: Optional[Dict[str, object]] = None):
if not meta:
meta = {}
meta["include_optimizer"] = include_optimizer
os.makedirs(path + "/assets", exist_ok=True)
with open(f"{path}/assets/saved_model.json", "w") as f:
json.dump(json.loads(model.to_json()), f, indent=2)
with open(f"{path}/meta.json", "w") as f:
json.dump(meta, f, indent=2)
model.save(path, include_optimizer=include_optimizer)
def writeCSV2(variator: Variator, model: Model, counter=[0, 0]):
history = variator.histories[-1]
score = model.evaluate(tX, tY, verbose=0)
acc = history.history['acc'][-1]
val_acc = history.history['val_acc'][-1]
print("counter: " + str(counter[1]))
if score[1] > counter[1]:
counter[1] = score[1]
model_json = model.to_json()
with open("Models/JSON/modelEvCluster_Architecure.json",
"w") as json_file:
json_file.write(model_json)
# serialize weights to HDF5
model.save("Models/Weights/bestEvModelCluster.hd5")
with open("Logs/modelStats.csv", "a") as f:
if counter[0] == 0:
counter[0] += 1
f.write("Model,acc,val_acc,test_acc\n")
f.write(variator.currentParameters['modelName'] + "," + str(acc) +
"," + str(val_acc) + "," + str(score[1]))
f.write("\n")
def save_model_json(model: Model, log_dir):
filename = "{0}_config.json".format(model.name)
filename = os.path.join(log_dir, filename)
with open(filename, "w") as file:
file.write(model.to_json())