in recommenders/models/newsrec/newsrec_utils.py [0:0]
def check_type(config):
"""Check that the config parameters are the correct type
Args:
config (dict): Configuration dictionary.
Raises:
TypeError: If the parameters are not the correct type.
"""
int_parameters = [
"word_size",
"his_size",
"title_size",
"body_size",
"npratio",
"word_emb_dim",
"attention_hidden_dim",
"epochs",
"batch_size",
"show_step",
"save_epoch",
"head_num",
"head_dim",
"user_num",
"filter_num",
"window_size",
"gru_unit",
"user_emb_dim",
"vert_emb_dim",
"subvert_emb_dim",
]
for param in int_parameters:
if param in config and not isinstance(config[param], int):
raise TypeError("Parameters {0} must be int".format(param))
float_parameters = ["learning_rate", "dropout"]
for param in float_parameters:
if param in config and not isinstance(config[param], float):
raise TypeError("Parameters {0} must be float".format(param))
str_parameters = [
"wordEmb_file",
"wordDict_file",
"userDict_file",
"vertDict_file",
"subvertDict_file",
"method",
"loss",
"optimizer",
"cnn_activation",
"dense_activation" "type",
]
for param in str_parameters:
if param in config and not isinstance(config[param], str):
raise TypeError("Parameters {0} must be str".format(param))
list_parameters = ["layer_sizes", "activation"]
for param in list_parameters:
if param in config and not isinstance(config[param], list):
raise TypeError("Parameters {0} must be list".format(param))
bool_parameters = ["support_quick_scoring"]
for param in bool_parameters:
if param in config and not isinstance(config[param], bool):
raise TypeError("Parameters {0} must be bool".format(param))