class_docstr: Megatron Vision Transformer Model.
class_docstr_tok: ["Megatron","Vision","Transformer","Model","."]
code: def list_available_models(cls) -> Optional[PretrainedModelInfo]:
      return None
  
imports: import itertools
  from functools import partial
  from typing import Any, Optional
  import torch
  from omegaconf.dictconfig import DictConfig
  from pytorch_lightning.accelerators import CPUAccelerator
  from pytorch_lightning.trainer.trainer import Trainer
  from nemo.collections.nlp.data.language_modeling.megatron.data_samplers import MegatronPretrainingSampler
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.build_model import build_model
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module, MegatronModule
  from nemo.collections.nlp.modules.common.megatron.utils import average_losses_across_data_parallel_group, get_all_params_for_weight_decay_optimization, get_linear_layer, get_params_for_weight_decay_optimization, init_method_normal, scaled_init_method_normal
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank, torch_dtype_from_precision
  from nemo.collections.vision.data.megatron.data_samplers import MegatronVisionPretrainingRandomSampler
  from nemo.collections.vision.data.megatron.vit_dataset import build_train_valid_datasets
  from nemo.collections.vision.modules.vit.vit_backbone import VitBackbone, VitMlpHead
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging
label_desc: Use image node_id 29 for calling the MegatronVitClassificationModel obj's underlying member method code with example usage: obj.list_available_models(cls) and returns: None