code: def _logit_bernoulli_entropy(
      logits: networks_lib.Logits,
  ) -> jnp.ndarray:
      return (
          1.0 - jax.nn.sigmoid(logits)
      ) * logits - jax.nn.log_sigmoid(logits)
  
file_path: acme/acme/agents/jax/ail/losses.py
imports: import functools
  from typing import Callable, Dict, Optional, Tuple
  from acme import types
  from acme.jax import networks
  import jax
  import jax.numpy
  import tensorflow_probability
  import tree
label_desc: Use image node_id 4 for calling a global function with example usage: _logit_bernoulli_entropy(logits) and returns: unknown