def load_model_file(model_file):
model_stuff = data.load_checkpoint(model_file)
opt = utils.convert_nested_dict_to_DD(model_stuff["opt"])
state_dict = model_stuff["state_dict"]
vocab = model_stuff['vocab']
return opt, state_dict, vocab
args = parser.parse_args()
split = args.split
# Generate configuration files depending on experiment being run
utils.generate_config_files("atomic", args.experiment_num, eval_mode=True)
# Loads the correct configuration file
config_file = "config/atomic/config_{}.json".format(args.experiment_num)
# Read config file to option
config = cfg.read_config(cfg.load_config(config_file))
cfg.device = config.gpu_index
eval_opt = cfg.get_eval_parameters(config)
model_stuff = data.load_checkpoint(args.model_name)
opt = model_stuff["opt"]
opt.eval.update(eval_opt)
opt.train.dynamic.epoch = 0
print("Loading Data")
categories = opt.data.categories
path = "data/atomic/processed/generation/{}.pickle".format(
utils.make_name_string(opt.data))
data_loader = data.make_data_loader(opt, categories)
loaded = data_loader.load_data(path)
# eval_mode = True means changes are taken from config/atomic/eval_changes.json
utils.generate_config_files("atomic", args.experiment_num, eval_mode=True)
# Loads the correct configuration file
config_file = "config/atomic/config_{}.json".format(args.experiment_num)
print(config_file)
# Read config file to option
config = cfg.read_config(cfg.load_config(config_file))
cfg.device = config.gpu_index
eval_opt = cfg.get_eval_parameters(config)
# Batch multiple models
model_file = data.load_checkpoint(args.model_name)
opt = model_file["opt"]
opt.eval.update(eval_opt)
print("Loading Data")
# Do multiple sets of categories:
# compute individual perplexity of categories in addition to total perplexity
if len(opt.data.categories) == 1:
set_of_categories = [opt.data.categories]
else:
set_of_categories = [opt.data.categories] + [[i]
for i in opt.data.categories]
print(set_of_categories)
def load_model_file(model_file):
model_stuff = data.load_checkpoint(model_file)
opt = model_stuff["opt"]
state_dict = model_stuff["state_dict"]
return opt, state_dict