class_docstr: Vision Transformer model for multi-label classification task.
class_docstr_tok: ["Vision","Transformer","model","for","multi-label","classification","task","."]
code: def default_flax_model_config(self) -> ml_collections.ConfigDict:
      return ml_collections.ConfigDict(
          {
              "model": dict(
                  num_heads=2,
                  num_layers=1,
                  representation_size=None,
                  mlp_dim=64,
                  dropout_rate=0.0,
                  attention_dropout_rate=0.0,
                  positional_embedding="learned_1d",
                  hidden_size=16,
                  patches={"size": (4, 4)},
                  classifier="token",
                  data_dtype_str="float32",
                  freeze_backbone=False,
                  use_batch_norm_after_encoder=True,
              ),
          }
      )
  
imports: from typing import Any, Callable, Optional, Sequence
  import flax.linen
  import jax
  import jax.numpy
  import ml_collections
  from scenic.model_lib.base_models import classification_model
  from scenic.model_lib.base_models import multilabel_classification_model
  from scenic.model_lib.layers import attention_layers
  from scenic.model_lib.layers import nn_layers
  from scenic.projects.av_mae import base_model
  from scenic.projects.av_mae import model_utils
  from scenic.projects.baselines import vit
label_desc: Use image node_id 2 for calling the ViTMAEClassificationFinetuning obj's underlying member method code with example usage: obj.default_flax_model_config() and returns: ml_collections