code: def _get_augreg_cfg(params_path):
      model = params_path.split("/")[-1].split("-")[0]
      assert model in (
          "B_16",
          "B_32",
      ), "Currently only B/16 and B/32 models are supported."
      sz = {"B_16": 16, "B_32": 32}[model]
      return ml_collections.ConfigDict(
          dict(
              num_classes=0,
              mlp_dim=3072,
              num_layers=12,
              num_heads=12,
              hidden_size=768,
              classifier="token",
              patches=dict(size=(sz, sz)),
              dropout_rate=0.0,
              attention_dropout_rate=0.0,
          )
      )
  
imports: from typing import Any, Callable, Optional, Sequence
  from absl import logging
  import flax
  import flax.linen
  import jax
  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
  import scipy
  from tensorflow.io import gfile
label_desc: Use image node_id 1 for calling a global function with example usage: _get_augreg_cfg(params_path) and returns: ml_collections