code: def gamma(
      shape, scale=1.0, size=None, random_state=None, dtype=np.float32
  ):
      """
      Draw samples from a Gamma distribution.
  
      Parameters
      ----------
      shape : float or array_like of floats
          The shape of the gamma distribution. Must be non-negative.
          
      scale : float or array_like of floats, optional
          The scale of the gamma distribution. Must be non-negative. Default is equal to 1.
          
      size : int or tuple of ints, optional
          Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn.\
          If size is None (default), a single value is returned if shape and scale are both scalars.\
          Otherwise, np.broadcast(shape, scale).size samples are drawn.
          
      random_state : int or np.random.RandomState, optional
          If an integer is given, it will be used as seed value for creating a RandomState.
          
      dtype : str or dtype
          Returned data-type for the output array.
  
      Returns
      -------
      out : ndarray or scalar
          Drawn samples from the parameterized gamma distribution.
      """
      return (
          get_rng(random_state).gamma(shape, scale, size).astype(dtype)
      )
  
file_path: cornac/cornac/utils/init_utils.py
imports: import numpy
  from .common import get_rng
label_desc: Use image node_id 6 for calling a global function with example usage: gamma(shape, scale, size, random_state, dtype) and returns: get_rng