def verify_model(single_model,dataset):
is_verify = True
if isinstance(single_model,dict):
single_model = get_original_format(single_model)
single_model = format_into_normal_form(single_model)
if dataset =="cifar10":
train_model_cifar10(single_model,is_verify)
elif dataset == 'mnist':
train_model_mnist(single_model,is_verify)
def verify_model(single_model,dataset):
############################################################################
# FUNCTION DESCRIPTION: function to test single model
############################################################################
is_verify = True
if isinstance(single_model,dict):
single_model = get_original_format(single_model)
single_model = format_into_normal_form(single_model)
if dataset =="cifar10":
train_model_cifar10(single_model,is_verify)
elif dataset == 'mnist':
train_model_mnist(single_model,is_verify)
def train_new_model(data,action_array,dataset):
#print("______________________________________________________")
#print("_________________ CANNOT FIND A MATCH ________________")
#print("______________________________________________________")
# num_model = NUM_MODEL_FROM_EXPERIENCE_REPLAY
# if UPDATE_FROM_MEM_REPLAY:
# update_qtable_from_mem_replay(data,num_model,dataset)
# return 1
if dataset == "cifar10":
return train_model_cifar10(action_array)
elif dataset == "mnist":
return train_model_mnist(action_array)
def train_new_model(data,action_array,dataset):
############################################################################
# FUNCTION DESCRIPTION: function to train new model if Q agent unable to find
# from the experience replay.
############################################################################
if UPDATE_AFTER_FIND_NEW_MODEL:
update_qtable_from_mem_replay(data,NUM_MODEL_AFTER_FIND_NEW_MODEL,dataset)
if dataset == "cifar10":
return train_model_cifar10(action_array)
elif dataset == "mnist":
return train_model_mnist(action_array)
def train_new_model(data,action_array,dataset):
print("_________________ CANNOT FIND A MATCH _______________")
print("______________________________________________________")
# num_model = 5
# update_qtable_from_mem_replay(data,num_model,dataset)
# print("LENGTH_DATA :::::::::::::::::::: ", len(data))
# return 1
# return random.uniform(0.70,0.75)
# print("action_array: ",action_array)
# return get_from_mem_replay(data,action_array)
if dataset == "cifar10":
return train_model_cifar10(action_array)
elif dataset == "mnist":
return train(action_array)