code: def convert_bert_mlm_head_params(
      tf_params: dict[str, tf.Tensor], prefix: str
  ) -> dict[str, Any]:
      return {
          "dense": bert_checkpoint_converter.convert_dense_layer_params(
              tf_params, f"{prefix}transform/dense/"
          ),
          "layer_norm": bert_checkpoint_converter.convert_layer_norm_params(
              tf_params, f"{prefix}transform/LayerNorm/"
          ),
          **bert_checkpoint_converter.param_conversion_util.convert_tf_params(
              tf_params, {("bias",): "output_bias"}, prefix
          ),
      }
  
imports: import dataclasses
  from typing import Any
  from typing import Optional
  from typing import Union
  import flax
  from flax.core import frozen_dict
  import flax.linen
  import jax
  import jax.numpy
  from scenic.projects.lang4video.model.base_encoders import TextEncoder
  import tensorflow
  from flaxformer.architectures.bert import bert
  from flaxformer.architectures.bert import bert_checkpoint_converter
  import flaxformer.architectures.bert.configs
  import flaxformer.architectures.bert.heads
label_desc: Use image node_id 1 for calling a global function with example usage: convert_bert_mlm_head_params(tf_params, prefix) and returns: dict