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,