class_docstr: Transformer MLP / feed-forward block.
  
  Args:
    config: TransformerConfig dataclass containing hyperparameters.
    out_dim: optionally specify out dimension.
docstr: Applies Transformer MlpBlock module.
docstr_tok: ["Applies","Transformer","MlpBlock","module","."]
code: def __call__(
      self, inputs: jax.Array, *, rngs: nnx.Rngs | None = None
  ):
      """Applies Transformer MlpBlock module."""
      x = self.linear1(inputs)
      x = nnx.relu(x)
      x = self.dropout(x, rngs=rngs)
      output = self.linear2(x)
      output = self.dropout(output, rngs=rngs)
      return output
  
imports: from __future__ import annotations
  import dataclasses
  from typing import Any, Optional
  import jax
  import jax.numpy
  import numpy
  from jax import lax
  from flax.experimental import nnx
  from flax.experimental.nnx.nnx import flaglib
  from flax.experimental.nnx.examples.lm1b.configs import default
label_desc: Use image node_id 2 for calling the MlpBlock obj's underlying member method code with example usage: obj.__call__(inputs) and returns: output