class_docstr: Simple feedforward MLP torso with initial layer-norm.
  
  This MLP's first linear layer is followed by a LayerNorm layer and a tanh
  non-linearity; subsequent layers use `activation`, which defaults to elu.
  
  Note! The default activation differs from the usual MLP default of ReLU for
  legacy reasons.
class_docstr_tok: ["Simple","feedforward","MLP","torso","with","initial","layer-norm",".","This","MLP","'s","first","linear","layer","is","followed","by","a","LayerNorm","layer","and","a","tanh","non-linearity",";","subsequent","layers","use","`","activation","`",",","which","defaults","to","elu",".","Note","!","The","default","activation","differs","from","the","usual","MLP","default","of","ReLU","for","legacy","reasons","."]
docstr: Forwards the policy network.
docstr_tok: ["Forwards","the","policy","network","."]
code: def __call__(self, inputs: jnp.ndarray) -> jnp.ndarray:
      """Forwards the policy network."""
      return self._network(inputs)
  
file_path: acme/acme/jax/networks/continuous.py
imports: from typing import Callable, Sequence
  import haiku
  import jax
  import jax.numpy
label_desc: Use image node_id 2 for calling the LayerNormMLP obj's underlying member method code with example usage: obj.__call__(inputs) and returns: self