class_docstr: [`FlaxLogitsWarper`] that performs top-p, i.e. restricting to top tokens summing to prob_cut_off <= prob_cut_off.
  
  Args:
      top_p (`float`):
          If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
          higher are kept for generation.
      filter_value (`float`, *optional*, defaults to -inf):
          All filtered values will be set to this float value.
      min_tokens_to_keep (`int`, *optional*, defaults to 1):
          Minimum number of tokens that cannot be filtered.
code: def __init__(
      self,
      top_p: float,
      filter_value: float = -float("Inf"),
      min_tokens_to_keep: int = 1,
  ):
      if not isinstance(top_p, float) or (top_p < 0 or top_p > 1.0):
          raise ValueError(
              f"`top_p` has to be a float > 0 and < 1, but is {top_p}"
          )
      if not isinstance(min_tokens_to_keep, int) or (
          min_tokens_to_keep < 1
      ):
          raise ValueError(
              f"`min_tokens_to_keep` has to be a positive integer, but is {min_tokens_to_keep}"
          )
  
      self.top_p = top_p
      self.filter_value = filter_value
      self.min_tokens_to_keep = min_tokens_to_keep
  
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 FlaxTopPLogitsWarper object from inherited base classes: FlaxLogitsWarper with example: obj = FlaxTopPLogitsWarper(top_p, filter_value, min_tokens_to_keep)