{'autoaugment': 1, 
 'backbone': 'vit_base_patch32', 
 'batch_size': 8, 
 'beta1': 0.9, 
 'beta2': 0.999, 
 'class_num': 100, 
 'config_path': 'vit_patch32_imagenet2012_config_standalone.yml', 
 'crop_min': 0.05, 
 'dataset_path': '/data/zx_cv/vit/models-master/VIT/cache/datasets/imagenet_cifa/tiny-new/datasets/train', 
 'enable_modelarts': 0, 
 'eval_batch_size': 4, 
 'eval_image_size': 224, 
 'eval_interval': 1, 
 'eval_num_workers': 2, 
 'eval_offset': -1, 
 'eval_path': '/data/zx_cv/vit/models-master/VIT/cache/datasets/imagenet_cifa/tiny-new/datasets/val', 
 'gc_flag': 0, 
 'interpolation': 'BILINEAR', 
 'keep_checkpoint_max': 3, 
 'label_smooth_factor': 0.1, 
 'loss_name': 'ce_smooth_mixup', 
 'loss_scale': 1024, 
 'lr_decay_mode': 'cosine', 
 'lr_init': 0.001, 
 'lr_max': 0.00044375, 
 'lr_min': 1e-08, 
 'max_epoch': 300, 
 'mixup': 0.2, 
 'no_weight_decay_filter': 'beta,bias', 
 'open_profiler': 0, 
 'opt': 'adamw', 
 'pretrained': '', 
 'save_checkpoint': 1, 
 'save_checkpoint_epochs': 8, 
 'save_checkpoint_path': './outputs', 
 'train_image_size': 224, 
 'train_num_workers': 1, 
 'use_label_smooth': 1, 
 'vit_config_path': 'src.vit.VitConfig', 
 'warmup_epochs': 0, 
 'weight_decay': 0.05} 
Please check the above information for the configurations 
standalone training 
######################################## 
{'auto_tune': 0, 
 'autoaugment': 1, 
 'aux_factor': 0.4, 
 'backbone': 'vit_base_patch32', 
 'batch_size': 8, 
 'beta1': 0.9, 
 'beta2': 0.999, 
 'class_num': 100, 
 'config_path': 'vit_patch32_imagenet2012_config_standalone.yml', 
 'crop_min': 0.05, 
 'dataset_name': 'imagenet', 
 'dataset_path': '/data/zx_cv/vit/models-master/VIT/cache/datasets/imagenet_cifa/tiny-new/datasets/train', 
 'device_id': 0, 
 'device_num': 1, 
 'enable_modelarts': 0, 
 'eval_batch_size': 4, 
 'eval_engine': 'imagenet', 
 'eval_image_size': 224, 
 'eval_interval': 1, 
 'eval_num_workers': 2, 
 'eval_offset': 0, 
 'eval_path': '/data/zx_cv/vit/models-master/VIT/cache/datasets/imagenet_cifa/tiny-new/datasets/val', 
 'gc_flag': 0, 
 'interpolation': 'BILINEAR', 
 'keep_checkpoint_max': 3, 
 'label_smooth_factor': 0.1, 
 'local_rank': 0, 
 'logger': <LOGGER mindspore-benchmark (NOTSET)>, 
 'loss_name': 'ce_smooth_mixup', 
 'loss_scale': 1024, 
 'lr_decay_mode': 'cosine', 
 'lr_init': 0.001, 
 'lr_max': 0.00044375, 
 'lr_min': 1e-08, 
 'max_epoch': 300, 
 'mixup': 0.2, 
 'no_weight_decay_filter': 'beta,bias', 
 'open_profiler': 0, 
 'opt': 'adamw', 
 'poly_power': 2, 
 'pretrained': '', 
 'save_checkpoint': 1, 
 'save_checkpoint_epochs': 8, 
 'save_checkpoint_path': './outputs', 
 'seed': 1, 
 'split_point': 0.4, 
 'train_image_size': 224, 
 'train_num_workers': 1, 
 'use_label_smooth': 1, 
 'vit_config_path': 'src.vit.VitConfig', 
 'warmup_epochs': 0, 
 'weight_decay': 0.05} 
######################################## 
get vit_config_path 
split_point=0.4 
============================================================ 
{'auto_tune': 0, 
 'autoaugment': 1, 
 'aux_factor': 0.4, 
 'backbone': 'vit_base_patch32', 
 'batch_size': 8, 
 'beta1': 0.9, 
 'beta2': 0.999, 
 'class_num': 100, 
 'config_path': 'vit_patch32_imagenet2012_config_standalone.yml', 
 'crop_min': 0.05, 
 'dataset_name': 'imagenet', 
 'dataset_path': '/data/zx_cv/vit/models-master/VIT/cache/datasets/imagenet_cifa/tiny-new/datasets/train', 
 'device_id': 0, 
 'device_num': 1, 
 'enable_modelarts': 0, 
 'eval_batch_size': 4, 
 'eval_engine': 'imagenet', 
 'eval_image_size': 224, 
 'eval_interval': 1, 
 'eval_num_workers': 2, 
 'eval_offset': 0, 
 'eval_path': '/data/zx_cv/vit/models-master/VIT/cache/datasets/imagenet_cifa/tiny-new/datasets/val', 
 'gc_flag': 0, 
 'interpolation': 'BILINEAR', 
 'keep_checkpoint_max': 3, 
 'label_smooth_factor': 0.1, 
 'local_rank': 0, 
 'logger': <LOGGER mindspore-benchmark (NOTSET)>, 
 'loss_name': 'ce_smooth_mixup', 
 'loss_scale': 1024, 
 'lr_decay_mode': 'cosine', 
 'lr_init': 0.001, 
 'lr_max': 0.00044375, 
 'lr_min': 1e-08, 
 'max_epoch': 300, 
 'mixup': 0.2, 
 'no_weight_decay_filter': 'beta,bias', 
 'open_profiler': 0, 
 'opt': 'adamw', 
 'poly_power': 2, 
 'pretrained': '', 
 'save_checkpoint': 1, 
 'save_checkpoint_epochs': 8, 
 'save_checkpoint_path': './outputs', 
 'seed': 1, 
 'split_point': 0.4, 
 'train_image_size': 224, 
 'train_num_workers': 1, 
 'use_label_smooth': 1, 
 'vit_config_path': 'src.vit.VitConfig', 
 'warmup_epochs': 0, 
 'weight_decay': 0.05} 
============================================================

[WARNING] ME(77569:281472473717680,MainProcess):2024-06-17-11:51:14.243.862 [mindspore/train/model.py:1108] For StateMonitor callback, {'step_end', 'epoch_end', 'epoch_begin'} methods may not be supported in later version, Use methods prefixed with 'on_train' or 'on_eval' instead when using customized callbacks. 
[ERROR] MD(77569,fffc7b7ef200,python3):2024-06-17-11:51:15.159.685 [mindspore/ccsrc/minddata/dataset/util/task_manager.cc:227] InterruptMaster] MindSpore dataset is terminated with err msg: Exception thrown from dataset pipeline. Refer to 'Dataset Pipeline Error Message'. map operation: [OneHot] failed. OneHot: index values should not bigger than num classes: 100, but got: 100 
Line of code : 49 
File         : mindspore/ccsrc/minddata/dataset/kernels/data/data_utils.cc