code: def __init__(
      self,
      config: BertConfig,
      input_shape: Tuple = (1, 1),
      seed: int = 0,
      dtype: jnp.dtype = jnp.float32,
      **kwargs,
  ):
      module = FlaxPerformerForMaskedLMModule(
          vocab_size=config.vocab_size,
          type_vocab_size=config.type_vocab_size,
          hidden_size=config.hidden_size,
          intermediate_size=config.intermediate_size,
          head_size=config.hidden_size,
          num_heads=config.num_attention_heads,
          num_encoder_layers=config.num_hidden_layers,
          max_length=config.max_position_embeddings,
          hidden_act=config.hidden_act,
          **kwargs,
      )
  
      super().__init__(
          config,
          module,
          input_shape=input_shape,
          seed=seed,
          dtype=dtype,
      )
  
imports: from typing import Callable, Dict, Tuple
  import flax.linen
  import jax
  import jax.numpy
  import numpy
  from jax.random import PRNGKey
  from modeling_flax_performer_utils import make_fast_softmax_attention
  from transformers.file_utils import add_start_docstrings
  from transformers.modeling_flax_utils import ACT2FN
  from transformers.models.bert.configuration_bert import BertConfig
  from transformers.models.bert.modeling_flax_bert import FlaxBertOnlyMLMHead, FlaxBertPreTrainedModel
  from transformers.utils import logging
label_desc: Use image node_id 1 to create a new FlaxPerformerForMaskedLM object from inherited base classes: FlaxBertPreTrainedModel with example: obj = FlaxPerformerForMaskedLM(config, input_shape, seed, dtype)