code: def __call__(self, hidden_state, attention_mask):
      attention = FlaxPerformerAttention(
          self.num_heads, self.head_size, name="attention"
      )(hidden_state, attention_mask)
      intermediate = FlaxPerformerIntermediate(
          self.intermediate_size,
          name="intermediate",
          hidden_act=self.hidden_act,
      )(attention)
      output = FlaxPerformerOutput(name="output")(
          intermediate, attention
      )
  
      return output
  
imports: from typing import Callable, Dict, Tuple
  import numpy
  import flax.linen
  import jax
  import jax.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 for calling the FlaxPerformerLayer obj's underlying member method code with example usage: obj.__call__(hidden_state, attention_mask) and returns: output