class_docstr: A Text Classification model.
code: def setup(self):
      self.embedder = Embedder(
          vocab_size=self.vocab_size,
          embedding_size=self.embedding_size,
          dropout_rate=self.dropout_rate,
          word_dropout_rate=self.word_dropout_rate,
          unk_idx=self.unk_idx,
      )
      self.encoder = SimpleBiLSTM(hidden_size=self.hidden_size)
      self.classifier = AttentionClassifier(
          hidden_size=self.hidden_size,
          output_size=self.output_size,
          dropout_rate=self.dropout_rate,
      )
  
imports: from __future__ import annotations
  import functools
  from typing import Any, Callable, Optional
  from flax import linen
  import jax
  from jax import numpy
  from jax._src.typing import Array
label_desc: Use image node_id 1 for calling the TextClassifier obj's underlying member method code with example usage: obj.setup() without return types