class_docstr: [`FlaxLogitsProcessor`] that takes a list of pairs of integers which indicates a mapping from generation indices to
  token indices that will be forced before sampling. The processor will set their log probs to 0 and all other tokens
  to `-inf` so that they are sampled at their corresponding index.
  
  Args:
      force_token_map (`list`):
          Map giving token ids and indices where they will be forced to be sampled.
code: def __init__(self, force_token_map):
      force_token_map = dict(force_token_map)
      # Converts the dictionary of format {index: token} containing the tokens to be forced to an array, where the
      # index of the array corresponds to the index of the token to be forced, for XLA compatibility.
      # Indexes without forced tokens will have a negative value.
      force_token_array = (
          jnp.ones((max(force_token_map.keys()) + 1), dtype=jnp.int32)
          * -1
      )
      for index, token in force_token_map.items():
          if token is not None:
              force_token_array = force_token_array.at[index].set(token)
      self.force_token_array = jnp.int32(force_token_array)
  
imports: import inspect
  import jax
  import jax.lax
  import jax.numpy
  from ..utils import add_start_docstrings
  from ..utils.logging import get_logger
label_desc: Use image node_id 1 to create a new FlaxForceTokensLogitsProcessor object from inherited base classes: FlaxLogitsProcessor with example: obj = FlaxForceTokensLogitsProcessor(force_token_map)