class_docstr: A classifier that uses attention to summarize the inputs.
  
  Attributes:
    hidden_size: The hidden size of the MLP classifier.
    output_size: The number of output classes for the classifier.
    dropout_rate: The dropout rate applied over the encoded_inputs, the summary
      of the inputs, and inside the MLP. Applied when `deterministic` is False.
    deterministic: Disables dropout if True.
code: def setup(self):
      self.dropout_layer = nn.Dropout(rate=self.dropout_rate)
      self.keys_only_mlp_attention = KeysOnlyMlpAttention(
          hidden_size=self.hidden_size
      )
      self.mlp = MLP(
          hidden_size=self.hidden_size,
          output_size=self.output_size,
          output_bias=False,
          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 AttentionClassifier obj's underlying member method code with example usage: obj.setup() without return types