code: def binomial(n=1, p=0.5, shape=_Null, dtype=_Null, **kwargs):
      """Draw random samples from a binomial distribution.
  
      Samples are distributed according to a binomial distribution parametrized
      by *n* (number of trials) and *p* (success probability).
  
      Parameters
      ----------
      n : float or Symbol, optional
          Number of experiments, > 0.
      p : float or Symbol, optional
          Success probability in each experiment, >= 0 and <= 1.
      shape : int or tuple of ints, optional
          The number of samples to draw. If shape is, e.g., `(m, n)` and `n` and
          `p` are scalars, output shape will be `(m, n)`. If `n` and `p`
          are NDArrays with shape, e.g., `(x, y)`, then output will have shape
          `(x, y, m, n)`, where `m*n` samples are drawn for each `[n, p)` pair.
      dtype : {'float16', 'float32', 'float64'}, optional
          Data type of output samples. Default is 'float32'
  
      Returns
      -------
      Symbol
          If input `shape` has shape, e.g., `(m, n)` and `n` and `p` are scalars, output
          shape will be `(m, n)`. If `n` and `p` are NDArrays with shape, e.g.,
          `(x, y)`, then output will have shape `(x, y, m, n)`, where `m*n` samples are
          drawn for each `[n, p)` pair.
      """
      return _random_helper(
          _internal._random_binomial,
          _internal._sample_binomial,
          [n, 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 8 for calling a global function with example usage: binomial(n, p, shape, dtype) and returns: _random_helper