code: def gamma(
      alpha: Union[float, paddle.Tensor],
      beta: Union[float, paddle.Tensor],
      /,
      *,
      shape: Optional[Union[ivy.NativeShape, Sequence[int]]] = None,
      dtype: Optional[Union[paddle.dtype, ivy.Dtype]] = None,
      device: core.Place = None,
      seed: Optional[int] = None,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      raise IvyNotImplementedException()
  
file_path: ivy/ivy/functional/backends/paddle/experimental/random.py
imports: from typing import Optional, Union, Sequence
  import paddle
  from ivy import with_unsupported_device_and_dtypes
  from ivy.functional.backends.paddle import backend_version
  from ivy.utils.exceptions import IvyNotImplementedException
  from ivy.functional.ivy.random import _check_bounds_and_get_shape
  import ivy
  from paddle.device import core
  from ivy import with_supported_device_and_dtypes
label_desc: Use image node_id 3 for calling a global function with example usage: gamma() without return types