code: def _update_weights_using_cover(
      workers_cover: jnp.ndarray,
      jobs_cover: jnp.ndarray,
      weights: jnp.ndarray,
  ) -> jnp.ndarray:
      """Updates weights for hungarian matching using a cover.
  
      We first find the minimum uncovered weight. Then, we subtract this from all
      the uncovered weights, and add it to all the doubly covered weights.
  
      Args:
        workers_cover: A boolean array of shape [b, n, 1].
        jobs_cover: A boolean array of shape [b, 1, n].
        weights: A float32 [b, n, n] array, where each inner matrix represents
          weights to be use for matching.
  
      Returns:
        A new weight matrix with elements adjusted by the cover.
      """
      max_value = jnp.max(weights)
  
      covered = jnp.logical_or(workers_cover, jobs_cover)
      double_covered = jnp.logical_and(workers_cover, jobs_cover)
  
      uncovered_weights = jnp.where(
          covered, jnp.full_like(weights, max_value), weights
      )
      min_weight = jnp.min(
          uncovered_weights, axis=(-2, -1), keepdims=True
      )
  
      add_weight = jnp.where(
          double_covered,
          jnp.full_like(weights, min_weight),
          jnp.zeros_like(weights),
      )
      sub_weight = jnp.where(
          covered,
          jnp.zeros_like(weights),
          jnp.full_like(weights, min_weight),
      )
  
      return weights + add_weight - sub_weight
  
file_path: scenic/scenic/model_lib/matchers/hungarian_cover.py
imports: from typing import Tuple, Optional, Dict
  import jax
  import jax.numpy
label_desc: Use image node_id 7 for calling a global function with example usage: _update_weights_using_cover(workers_cover, jobs_cover, weights) and returns: unknown