def get_params(test_config):
"""get params and save them to root dir"""
prm = Parameters()
# get giles paths
prm.override(test_config)
test_parameter_file = os.path.join(prm.train.train_control.ROOT_DIR,
'test_parameters.ini')
log_file = os.path.join(prm.train.train_control.ROOT_DIR, 'test.log')
ret = True
if os.path.isfile(test_parameter_file):
warnings.warn('Test parameter file {} already exists'.format(
test_parameter_file))
ret = query_yes_no('Overwrite parameter file?')
if ret:
dir = os.path.dirname(test_parameter_file)
if not os.path.exists(dir):
os.makedirs(dir)
prm.save(test_parameter_file)
logging = logging_config(log_file)
logging.disable(logging.DEBUG)
return prm
def get_params(test_config):
"""get params and save them to root dir"""
prm = Parameters()
# get giles paths
prm.override(test_config) # just to get the LOG_DIR_LIST[0]
train_log_dir = prm.test.ensemble.LOG_DIR_LIST[0]
parameter_file = os.path.join(train_log_dir, 'parameters.ini')
test_parameter_file = os.path.join(prm.train.train_control.ROOT_DIR,
'test_parameters.ini')
all_parameter_file = os.path.join(prm.train.train_control.ROOT_DIR,
'all_parameters.ini')
log_file = os.path.join(prm.train.train_control.ROOT_DIR, 'test.log')
if not os.path.isfile(parameter_file):
raise AssertionError('Can not find file: {}'.format(parameter_file))
ret = True
if os.path.isfile(test_parameter_file):
warnings.warn('Test parameter file {} already exists'.format(
test_parameter_file))
ret = query_yes_no('Overwrite parameter file?')
if ret:
dir = os.path.dirname(test_parameter_file)
if not os.path.exists(dir):
os.makedirs(dir)
prm.save(test_parameter_file)
logging = logging_config(log_file)
logging.disable(logging.DEBUG)
# Done saving test parameters. Now doing the integration:
prm = Parameters()
prm.override(parameter_file)
prm.override(test_parameter_file)
ret = True
if os.path.isfile(all_parameter_file):
warnings.warn(
'All parameter file {} already exists'.format(all_parameter_file))
ret = query_yes_no('Overwrite parameter file?')
if ret:
dir = os.path.dirname(all_parameter_file)
if not os.path.exists(dir):
os.makedirs(dir)
prm.save(all_parameter_file)
return prm
def get_params(test_config, parser_args=None):
"""get params and save them to root dir"""
# Just to get the ROOT_DIR and save prm test_config
prm = Parameters()
prm.override(test_config)
# get manual test parameters from config:
if parser_args is not None:
# overriding some parameters manually from parser:
prm.train.train_control.ROOT_DIR = parser_args.ROOT_DIR
prm.train.train_control.TEST_DIR = parser_args.ROOT_DIR + '/test'
prm.train.train_control.PREDICTION_DIR = parser_args.ROOT_DIR + '/prediction'
prm.train.train_control.CHECKPOINT_DIR = parser_args.ROOT_DIR + '/checkpoint'
prm.test.test_control.KNN_WEIGHTS = parser_args.KNN_WEIGHTS
prm.test.test_control.KNN_NORM = parser_args.KNN_NORM
prm.train.train_control.PCA_REDUCTION = (
parser_args.PCA_REDUCTION == 'True')
prm.train.train_control.PCA_EMBEDDING_DIMS = int(
parser_args.PCA_EMBEDDING_DIMS)
prm.test.test_control.KNN_NEIGHBORS = int(parser_args.KNN_NEIGHBORS)
prm.test.test_control.DUMP_NET = (parser_args.DUMP_NET == 'True')
prm.test.test_control.LOAD_FROM_DISK = (
parser_args.LOAD_FROM_DISK == 'True')
ROOT_DIR = prm.train.train_control.ROOT_DIR
# get time stamp
ts = get_timestamp()
# get files paths
parameter_file = os.path.join(ROOT_DIR, 'parameters.ini')
test_parameter_file = os.path.join(ROOT_DIR,
'test_parameters_' + ts + '.ini')
all_parameter_file = os.path.join(ROOT_DIR,
'all_parameters_' + ts + '.ini')
log_file = os.path.join(ROOT_DIR, 'test_' + ts + '.log')
logging = logging_config(log_file)
logging.disable(logging.DEBUG)
if not os.path.isfile(parameter_file):
raise AssertionError('Can not find file: {}'.format(parameter_file))
dir = os.path.dirname(test_parameter_file)
if not os.path.exists(dir):
os.makedirs(dir)
prm.save(test_parameter_file)
# Done saving test parameters. Now doing the integration:
prm = Parameters()
prm.override(parameter_file)
prm.override(test_parameter_file)
if parser_args is not None:
# overriding some parameters manually from parser:
prm.train.train_control.ROOT_DIR = parser_args.ROOT_DIR
prm.train.train_control.TEST_DIR = parser_args.ROOT_DIR + '/test'
prm.train.train_control.PREDICTION_DIR = parser_args.ROOT_DIR + '/prediction'
prm.train.train_control.CHECKPOINT_DIR = parser_args.ROOT_DIR + '/checkpoint'
prm.test.test_control.KNN_WEIGHTS = parser_args.KNN_WEIGHTS
prm.test.test_control.KNN_NORM = parser_args.KNN_NORM
prm.train.train_control.PCA_REDUCTION = (
parser_args.PCA_REDUCTION == 'True')
prm.train.train_control.PCA_EMBEDDING_DIMS = int(
parser_args.PCA_EMBEDDING_DIMS)
prm.test.test_control.KNN_NEIGHBORS = int(parser_args.KNN_NEIGHBORS)
prm.test.test_control.DUMP_NET = (parser_args.DUMP_NET == 'True')
prm.test.test_control.LOAD_FROM_DISK = (
parser_args.LOAD_FROM_DISK == 'True')
dir = os.path.dirname(all_parameter_file)
if not os.path.exists(dir):
os.makedirs(dir)
prm.save(all_parameter_file)
return prm
from utils.data import Data
from utils.senticap_data import SenticapData
from utils.parameters import Parameters
from ops.inference import inference
from vae_model.classifier import Classifier
from vae_model.encoder import Encoder
from vae_model.decoder import Decoder
# os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
# os.environ["CUDA_VISIBLE_DEVICES"]='1'
# parameters
params = Parameters()
params.parse_args()
n_classes = params.n_classes
if params.save_params:
params.save()
# data
global_step = tf.Variable(0, trainable=False, name="gl_step")
images_dir = params.images_dir
if params.data == "stylenet":
data = Data(images_dir,
params,
keep_words=params.keep_words,
all_30k_set=params.use_f30k,
partial=params.add_f,
vocab_fn=params.checkpoint)
elif params.data == "senticap":
IMAGES_DIR = "/home/luoyy16/datasets-large/mscoco/coco/images/"
SENTICAP_DIR = "./senticap"
data = SenticapData(IMAGES_DIR,
params,
