code: def _binary_cross_entropy_loss(
      logit: jnp.ndarray, label: jnp.ndarray
  ) -> jnp.ndarray:
      return label * jax.nn.softplus(-logit) + (
          1 - label
      ) * jax.nn.softplus(logit)
  
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 1 for calling a global function with example usage: _binary_cross_entropy_loss(logit, label) and returns: unknown