def get_trainer_by_name(name, param_dict, rest_args): if name == 'normal': param_dict['num_epoch'] = args.num_epoch return Trainer(**param_dict) num_minibatch = util.string_to_int_list(args.num_minibatch) if len(num_minibatch) == 1: param_dict['num_minibatch'] = num_minibatch[0] else: param_dict['num_minibatch'] = num_minibatch if name == 'minibatch': return MiniBatchTrainer(**param_dict) if name == 'catewise': param_dict['num_caterange_list'] = util.string_to_int_list(args.num_caterange_list) return ImageNetCatewisedTrainer(**param_dict) if name == 'categroup': param_dict['num_group_list'] = util.string_to_int_list(args.num_group_list) return ImageNetCateGroupTrainer(**param_dict) raise Exception, 'No trainer found for name: %s' % name
if not getattr(args, a) and a not in extra_argument: assert False, 'You have to specify a value of %s' % a param_dict = {} param_dict['image_color'] = 3 param_dict['test_id'] = args.test_id param_dict['data_dir'] = args.data_dir param_dict['data_provider'] = args.data_provider if args.data_provider.startswith('imagenet'): param_dict['image_size'] = 224 elif args.data_provider.startswith('cifar'): param_dict['image_size'] = 32 else: assert False, 'Unknown data_provider %s' % args.data_provider param_dict['train_range'] = util.string_to_int_list(args.train_range) param_dict['test_range'] = util.string_to_int_list(args.test_range) param_dict['save_freq'] = args.save_freq param_dict['test_freq'] = args.test_freq param_dict['adjust_freq'] = args.adjust_freq factor = util.string_to_float_list(args.factor) if len(factor) == 1: param_dict['factor'] = factor[0] else: param_dict['factor'] = factor learning_rate = util.string_to_float_list(args.learning_rate) if len(learning_rate) == 1: param_dict['learning_rate'] = learning_rate[0] else: param_dict['learning_rate'] = learning_rate
assert False, 'You have to specify a value of %s' % a param_dict = {} param_dict['image_color'] = 3 param_dict['test_id'] = args.test_id param_dict['data_dir'] = args.data_dir param_dict['data_provider'] = args.data_provider if args.data_provider.startswith('imagenet'): param_dict['image_size'] = 224 elif args.data_provider.startswith('cifar'): param_dict['image_size'] = 32 else: assert False, 'Unknown data_provider %s' % args.data_provider param_dict['train_range'] = util.string_to_int_list(args.train_range) param_dict['test_range'] = util.string_to_int_list(args.test_range) param_dict['save_freq'] = args.save_freq param_dict['test_freq'] = args.test_freq param_dict['adjust_freq'] = args.adjust_freq factor = util.string_to_float_list(args.factor) if len(factor) == 1: param_dict['factor'] = factor[0] else: param_dict['factor'] = factor learning_rate = util.string_to_float_list(args.learning_rate) if len(learning_rate) == 1: param_dict['learning_rate'] = learning_rate[0] else:
assert False, 'You have to specify a value of %s' % a param_dict = {} param_dict['image_color'] = 3 param_dict['test_id'] = args.test_id param_dict['data_dir'] = args.data_dir param_dict['data_provider'] = args.data_provider if args.data_provider.startswith('imagenet'): param_dict['image_size'] = 224 elif args.data_provider.startswith('cifar'): param_dict['image_size'] = 32 else: assert False, 'Unknown data_provider %s' % args.data_provider param_dict['train_range'] = util.string_to_int_list(args.train_range) param_dict['test_range'] = util.string_to_int_list(args.test_range) util.log('%s %s', args.test_range, param_dict['test_range']) param_dict['save_freq'] = args.save_freq param_dict['test_freq'] = args.test_freq param_dict['adjust_freq'] = args.adjust_freq factor = util.string_to_float_list(args.factor) if len(factor) == 1: param_dict['factor'] = factor[0] else: param_dict['factor'] = factor learning_rate = util.string_to_float_list(args.learning_rate) if len(learning_rate) == 1: param_dict['learning_rate'] = learning_rate[0]