def get_eval_parameters(opt, force_categories=None): evaluate = DD() if opt.eval_sampler == "beam": evaluate.bs = opt.beam_size elif opt.eval_sampler == "greedy": evaluate.bs = 1 elif opt.eval_sampler == "topk": evaluate.k = opt.topk_size evaluate.smax = opt.gen_seqlength evaluate.sample = opt.eval_sampler evaluate.numseq = opt.num_sequences evaluate.gs = opt.generate_sequences evaluate.es = opt.evaluate_sequences if opt.dataset == "atomic": if "eval_categories" in opt and force_categories is None: evaluate.categories = opt.eval_categories else: evaluate.categories = force_categories return evaluate
def get_data_parameters(opt, experiment, dataset): data = DD() if dataset == "atomic": data.categories = sorted(opt.categories) # hard-coded data.maxe1 = 17 data.maxe2 = 35 data.maxr = 1 elif dataset == "conceptnet": data.rel = opt.relation_format data.trainsize = opt.training_set_size data.devversion = opt.development_set_versions_to_use data.maxe1 = opt.max_event_1_size data.maxe2 = opt.max_event_2_size if data.rel == "language": # hard-coded data.maxr = 5 else: # hard-coded data.maxr = 1 elif dataset == "motiv_sent": data.categories = sorted(opt.categories) data.maxe1 = 100 data.maxe2 = 67 data.maxr = 1 return data
def get_data_parameters(opt, experiment, dataset):#####opt.exp & opt.data used for data loader path data = DD() ################## if dataset == "atomic": data.categories = sorted(opt.categories) #ORIGINAL CODE # hard-coded data.maxe1 = 17 data.maxe2 = 35 data.maxr = 1 #ADRIAN ADDED ################THIS IS WHERE YOU CHANGE PARAMETERS FOR NAME OF LOADER YOU'RE USING ##############MAXE1 == MAX EVENT ############MAXE2 == MAX EFFECT data.maxe1 = 50 data.maxe2 = 35 data.maxr = 1 ### elif dataset == "conceptnet": data.rel = opt.relation_format data.trainsize = opt.training_set_size data.devversion = opt.development_set_versions_to_use data.maxe1 = opt.max_event_1_size data.maxe2 = opt.max_event_2_size if data.rel == "language": # hard-coded data.maxr = 5 else: # hard-coded data.maxr = 1 return data############