code: def _gamma(
      shape, alpha, beta=None, dtype=np.float32, seed=None, name=None
  ):  # pylint: disable=unused-argument
      rng = (
          np.random
          if seed is None
          else np.random.RandomState(seed & 0xFFFFFFFF)
      )
      scale = 1.0 if beta is None else (1.0 / beta)
      shape = _ensure_shape_tuple(shape)
      return rng.gamma(shape=alpha, scale=scale, size=shape).astype(
          dtype
      )
  
imports: import numpy
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy.numpy_math import softmax
label_desc: Use image node_id 6 for calling a global function with example usage: _gamma(shape, alpha, beta, dtype, seed, name) and returns: rng