  
  
  _PARAMS = ["partial", "bias"]
  _VALUES = [(0.0, False), (0.25, False), (0.5, True), (0.75, False), (1.0, True)]
  _IDS = ["partial={}|bias={}[{}]".format(v[0], v[1], get_backend().upper())
          for v in _VALUES]
  
  
  @pytest.mark.parametrize(_PARAMS, _VALUES, ids=_IDS)
  def test_rms_normalization(partial, bias):  # pylint:disable=unused-argument
      """ Basic test for RMS Layer normalization. """
 
</s> remove _IDS = ["{}[{}]".format(loss, get_backend().upper()) for loss in _IDS]
 </s> add _IDS = [f"{loss}[{get_backend().upper()}]" for loss in _IDS] </s> remove _LWIDS = ["{}[{}]".format(loss, get_backend().upper()) for loss in _LWIDS]
 </s> add _LWIDS = [f"{loss}[{get_backend().upper()}]" for loss in _LWIDS] </s> remove             valid = [x for x in _MODEL_MAPPING if not _MODEL_MAPPING[x].get('no_amd')]
 </s> add             valid = [k for k, v in _MODEL_MAPPING.items() if not v.get('no_amd')] </s> remove                 ret.append(list())
 </s> add                 ret.append([])
_IDS = [f"partial={v[0]}|bias={v[1]}[{get_backend().upper()}]" for v in _VALUES]
  
  
  _PARAMS = ["partial", "bias"]
  _VALUES = [(0.0, False), (0.25, False), (0.5, True), (0.75, False), (1.0, True)]
_IDS = [f"partial={v[0]}|bias={v[1]}[{get_backend().upper()}]" for v in _VALUES]
_IDS = [f"partial={v[0]}|bias={v[1]}[{get_backend().upper()}]" for v in _VALUES]
  
  
  @pytest.mark.parametrize(_PARAMS, _VALUES, ids=_IDS)
  def test_rms_normalization(partial, bias):  # pylint:disable=unused-argument
      """ Basic test for RMS Layer normalization. """
keep keep keep keep replace replace keep keep keep keep keep
 Update all Keras Imports to be conditional (#1214)

* Remove custom keras importer

* first round keras imports fix

* launcher.py: Remove KerasFinder references

* 2nd round keras imports update (lib and extract)

* 3rd round keras imports update (train)

* remove KerasFinder from tests

* 4th round keras imports update (tests) 
tests/lib/model/normalization_test.py