class_docstr: A Zero Inflated Negative Binomial distribution.
  
  :param total_count: non-negative number of negative Bernoulli trials.
  :type total_count: float or torch.Tensor
  :param torch.Tensor probs: Event probabilities of success in the half open interval [0, 1).
  :param torch.Tensor logits: Event log-odds for probabilities of success.
  :param torch.Tensor gate: probability of extra zeros.
  :param torch.Tensor gate_logits: logits of extra zeros.
class_docstr_tok: ["A","Zero","Inflated","Negative","Binomial","distribution",".",":","param","total_count",":","non-negative","number","of","negative","Bernoulli","trials",".",":","type","total_count",":","float","or","torch.Tensor",":","param","torch.Tensor","probs",":","Event","probabilities","of","success","in","the","half","open","interval","[","0",",","1",")",".",":","param","torch.Tensor","logits",":","Event","log-odds","for","probabilities","of","success",".",":","param","torch.Tensor","gate",":","probability","of","extra","zeros",".",":","param","torch.Tensor","gate_logits",":","logits","of","extra","zeros","."]
code: def __init__(
      self,
      total_count,
      *,
      probs=None,
      logits=None,
      gate=None,
      gate_logits=None,
      validate_args=None,
  ):
      base_dist = NegativeBinomial(
          total_count=total_count,
          probs=probs,
          logits=logits,
          validate_args=False,
      )
      base_dist._validate_args = validate_args
  
      super().__init__(
          base_dist,
          gate=gate,
          gate_logits=gate_logits,
          validate_args=validate_args,
      )
  
imports: import torch
  from torch.distributions import constraints
  from torch.distributions.utils import broadcast_all, lazy_property, logits_to_probs, probs_to_logits
  from torch.nn.functional import softplus
  from pyro.distributions import NegativeBinomial, Poisson, TorchDistribution
  from pyro.distributions.util import broadcast_shape
label_desc: Use image node_id 1 to create a new ZeroInflatedNegativeBinomial object from inherited base classes: ZeroInflatedDistribution with example: obj = ZeroInflatedNegativeBinomial(total_count)