class_docstr: X-ViT model for multi-label classification task.
class_docstr_tok: ["X-ViT","model","for","multi-label","classification","task","."]
code: def default_flax_model_config(self):
      return ml_collections.ConfigDict(
          dict(
              model=dict(
                  attention_fn="standard",
                  attention_configs={"num_heads": 2},
                  transformer_encoder_configs={"type": "global"},
                  num_layers=1,
                  representation_size=16,
                  mlp_dim=32,
                  dropout_rate=0.0,
                  attention_dropout_rate=0.0,
                  hidden_size=16,
                  patches={"size": (4, 4)},
                  classifier="gap",
              ),
              data_dtype_str="float32",
          )
      )
  
imports: from typing import Any, Optional
  import flax.linen
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.model_lib.base_models.multilabel_classification_model import MultiLabelClassificationModel
  from scenic.model_lib.layers import attention_layers
  from scenic.model_lib.layers import nn_layers
  from scenic.model_lib.layers import nn_ops
  from scenic.projects.baselines import vit
  from scenic.projects.fast_vit import model_utils
label_desc: Use image node_id 2 for calling the XViTMultiLabelClassificationModel obj's underlying member method code with example usage: obj.default_flax_model_config() and returns: ml_collections