code: def negative_binomial(k=1, p=1, shape=_Null, dtype=_Null, **kwargs):
      """Draw random samples from a negative binomial distribution.
  
      Samples are distributed according to a negative binomial distribution
      parametrized by *k* (limit of unsuccessful experiments) and *p* (failure
      probability in each experiment). Samples will always be returned as a
      floating point data type.
  
      Parameters
      ----------
      k : float or Symbol, optional
          Limit of unsuccessful experiments, > 0.
      p : float or Symbol, optional
          Failure probability in each experiment, >= 0 and <=1.
      shape : int or tuple of ints
          The number of samples to draw. If shape is, e.g., `(m, n)` and `k` and
          `p` are scalars, output shape will be `(m, n)`. If `k` and `p`
          are Symbols with shape, e.g., `(x, y)`, then output will have shape
          `(x, y, m, n)`, where `m*n` samples are drawn for each `[k, p)` pair.
      dtype : {'float16', 'float32', 'float64'}, optional
          Data type of output samples. Default is 'float32'
  
      Returns
      -------
      Symbol
          If input `shape` has dimensions, e.g., `(m, n)`, and `k` and
          `p` are scalars, returned Symbol will resolve to shape `(m, n)`. If `k`
          and `p` are Symbols with shape, e.g., `(x, y)`, returned Symbol will resolve
          to shape `(x, y, m, n)`, where `m*n` samples are drawn for each `[k, p)` pair.
      """
      return _random_helper(
          _internal._random_negative_binomial,
          _internal._sample_negative_binomial,
          [k, p],
          shape,
          dtype,
          kwargs,
      )
  
file_path: mxnet/python/mxnet/symbol/random.py
imports: from ..base import numeric_types, _Null
  from .None import _internal
  from .symbol import Symbol
label_desc: Use image node_id 9 for calling a global function with example usage: negative_binomial(k, p, shape, dtype) and returns: _random_helper