test_dataloader=dict(batch_size=1,num_workers=4,persistent_workers=True,sampler=dict(type='DefaultSampler',shuffle=False),dataset=dict(type=dataset_type,data_root=data_root,data_prefix=dict(img_path='leftImg8bit/test',seg_map_path='gtFine/test'),pipeline=test_pipeline)) ...
( self, dataset: ConcatDataset, samples_per_gpu=1, num_replicas=None, rank=None, sample_ratio=None, by_prob=True, at_least_one=False, seed=0, max_iters=None, ): _rank, _num_replicas = get_dist_info() if num_replicas is None: num_replicas = _num_replicas if rank is None: ...
use_int8_training: print_rank_0( "training_args.use_int8_training!!! (int8 is not compatible with DeepSpeed)", log_file, global_rank, ) model = prepare_model_for_int8_training(model) config = LoraConfig( r=lora_config["lora_r"], lora_alpha=lora_config["lora_alpha"], # target_...