code: def predictions_match_labels(
      *, logits: jnp.ndarray, labels: jnp.ndarray, **kwargs
  ) -> jnp.ndarray:
      """Returns a binary array indicating where predictions match the labels."""
      del kwargs  # Unused.
      preds = logits > 0
      return (preds == labels).astype(jnp.float32)
  
imports: import os
  from typing import Any, Dict, Iterable, Tuple, Optional
  from absl import logging
  from clu import checkpoint
  from clu import metric_writers
  from clu import metrics
  from clu import parameter_overview
  from clu import periodic_actions
  import flax
  import flax.core
  import flax.linen
  from flax.training import train_state
  import jax
  import jax.numpy
  import jraph
  import ml_collections
  import numpy
  import optax
  import sklearn.metrics
  import tensorflow
  import input_pipeline
  import models
label_desc: Use image node_id 4 for calling a global function with example usage: predictions_match_labels() and returns: unknown