class_docstr: A Text Classification model.
docstr: Embeds the token IDs, encodes them, and classifies with attention.
code: def __call__(
      self,
      token_ids: Array,
      lengths: Array,
      deterministic: Optional[bool] = None,
  ) -> Array:
      """Embeds the token IDs, encodes them, and classifies with attention."""
      embedded_inputs = self.embed_token_ids(
          token_ids, deterministic=deterministic
      )
      logits = self.logits_from_embedded_inputs(
          embedded_inputs, lengths, deterministic=deterministic
      )
      return logits
  
imports: import functools
  from typing import Any, Callable, Optional
  from flax import linen
  import jax
  from jax import numpy
label_desc: Use image node_id 4 for calling the TextClassifier obj's underlying member method code with example usage: obj.__call__(token_ids, lengths, deterministic) and returns: logits