code: def _entropy(
      self, xp, scp, dtype, shape, use_qk, base, axis, normalize
  ):
      pk = testing.shaped_random(shape, xp, dtype=dtype)
      is_float16 = pk.dtype.char == "e"
      if use_qk:
          qk = testing.shaped_random(shape, xp, dtype=dtype)
      else:
          qk = None
  
      if normalize and pk.dtype.kind != "c":
          # if we don't normalize pk and qk, entropy will do it internally
          norm_axis = 0 if axis is None else axis
          pk = _distributions._normalize(pk, norm_axis)
          if qk is not None:
              qk = _distributions._normalize(qk, norm_axis)
      res = scp.stats.entropy(pk, qk=qk, base=base, axis=axis)
  
      float_type = xp.float32 if pk.dtype.char in "ef" else xp.float64
      if res.ndim > 0:
          # verify expected dtype
          assert res.dtype == float_type
  
      # Cast back to the floating precision of the input so that the
      # correct rtol is used by numpy_cupy_allclose
      res = xp.asarray(res, xp.float16 if is_float16 else float_type)
      return res
  
imports: import math
  import unittest
  import numpy
  import pytest
  import cupy
  from cupy import testing
  import cupyx.scipy.stats
  from cupyx.scipy import stats
  from cupyx.scipy.stats import _distributions
label_desc: Use image node_id 1 for calling the TestEntropy obj's underlying member method code with example usage: obj._entropy(xp, scp, dtype, shape, use_qk, base, axis, normalize) and returns: res