ValueError                                Traceback (most recent call last)
<ipython-input-59-dd135cdcecbf> in <module>
----> 1 loaded_model = mlflow.pyfunc.load_model('runs:/{0}/Model'.format(run_id))

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\mlflow\pyfunc\__init__.py in load_model(model_uri, suppress_warnings)
    290         mlflow.pyfunc.utils._add_code_to_system_path(code_path=code_path)
    291     data_path = os.path.join(local_model_path, conf[DATA]) if (DATA in conf) else local_model_path
--> 292     return importlib.import_module(conf[MAIN])._load_pyfunc(data_path)
    293
    294

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\mlflow\pyfunc\model.py in _load_pyfunc(model_path)
    212             "Python model path was not specified in the model configuration")
    213     with open(os.path.join(model_path, python_model_subpath), "rb") as f:
--> 214         python_model = cloudpickle.load(f)
    215
    216     artifacts = {}

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\network.py in __setstate__(self, state)
   1332
   1333     def __setstate__(self, state):
-> 1334         model = saving.unpickle_model(state)
   1335         self.__dict__.update(model.__dict__)
   1336

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\saving.py in unpickle_model(state)
    602 def unpickle_model(state):
    603     h5dict = H5Dict(state, mode='r')
--> 604     return _deserialize_model(h5dict)
    605
    606

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\saving.py in _deserialize_model(h5dict, custom_objects, compile)
    367                       weighted_metrics=weighted_metrics,
    368                       loss_weights=loss_weights,
--> 369                       sample_weight_mode=sample_weight_mode)
    370
    371         # Set optimizer weights.

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\backend\tensorflow_backend.py in symbolic_fn_wrapper(*args, **kwargs)
     73         if _SYMBOLIC_SCOPE.value:
     74             with get_graph().as_default():
---> 75                 return func(*args, **kwargs)
     76         else:
     77             return func(*args, **kwargs)

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\training.py in compile(self, optimizer, loss, metrics, loss_weights, sample_weight_mode, weighted_metrics, target_tensors, **kwargs)
    209
    210         # Save all metric attributes per output of the model.
--> 211         self._cache_output_metric_attributes(metrics, weighted_metrics)
    212
    213         # Set metric attributes on model.

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\training.py in _cache_output_metric_attributes(self, metrics, weighted_metrics)
    736                 output_shapes.append(list(output.shape))
    737         self._per_output_metrics = training_utils.collect_per_output_metric_info(
--> 738             metrics, self.output_names, output_shapes, self.loss_functions)
    739         self._per_output_weighted_metrics = (
    740             training_utils.collect_per_output_metric_info(

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\training_utils.py in collect_per_output_metric_info(metrics, output_names, output_shapes, loss_fns, is_weighted)
    941             metric_name = get_metric_name(metric, is_weighted)
    942             metric_fn = get_metric_function(
--> 943                 metric, output_shape=output_shapes[i], loss_fn=loss_fns[i])
    944
    945             # If the metric function is not stateful, we create a stateful version.

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\engine\training_utils.py in get_metric_function(metric, output_shape, loss_fn)
    984     """
    985     if metric not in ['accuracy', 'acc', 'crossentropy', 'ce']:
--> 986         return metrics_module.get(metric)
    987
    988     is_sparse_categorical_crossentropy = (

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\metrics.py in get(identifier)
   1976         return deserialize(config)
   1977     elif isinstance(identifier, six.string_types):
-> 1978         return deserialize(str(identifier))
   1979     elif callable(identifier):
   1980         return identifier

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\metrics.py in deserialize(config, custom_objects)
   1968                                     module_objects=globals(),
   1969                                     custom_objects=custom_objects,
-> 1970                                     printable_module_name='metric function')
   1971
   1972

c:\users\dscally\appdata\local\programs\python\python37\lib\site-packages\keras\utils\generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
    165             if fn is None:
    166                 raise ValueError('Unknown ' + printable_module_name +
--> 167                                  ':' + function_name)
    168         return fn
    169     else:

ValueError: Unknown metric function:custom_mse

​