Update and clean up of ml params

elephas/ml/params.py

@@ -3,39 +3,36 @@
 
 class HasKerasModelConfig(Params):
     '''
-    Mandatory:
+    Mandatory field:
 
     Parameter mixin for Keras model yaml
     '''
     def __init__(self):
         super(HasKerasModelConfig, self).__init__()
-        self.keras_model = Param(self, "keras_model", "Serialized Keras model as yaml string")
+        self.keras_model_config = Param(self, "keras_model_config", "Serialized Keras model as yaml string")
 
-    def set_keras_model(self, model):
-        self._paramMap[self.keras_model] = model
+    def set_keras_model_config(self, keras_model_config):
+        self._paramMap[self.keras_model_config] = keras_model_config
         return self
 
-    def get_keras_model(self):
-        return self.getOrDefault(self.keras_model)
+    def get_keras_model_config(self):
+        return self.getOrDefault(self.keras_model_config)
 
 
 class HasOptimizerConfig(Params):
     '''
-    Mandatory:
-
     Parameter mixin for Elephas optimizer config
     '''
     def __init__(self):
         super(HasOptimizerConfig, self).__init__()
         self.optimizer_config = Param(self, "optimizer_config", "Serialized Elephas optimizer properties")
-        # TODO: Define default value
 
-    def set_optimizer_config(self, optimizer):
-        self._paramMap[self.optimizer] = optimizer
+    def set_optimizer_config(self, optimizer_config):
+        self._paramMap[self.optimizer_config] = optimizer_config
         return self
 
     def get_optimizer_config(self):
-        return self.getOrDefault(self.config)
+        return self.getOrDefault(self.optimizer_config)
 
 
 class HasMode(Params):
@@ -72,7 +69,7 @@ def get_frequency(self):
         return self.getOrDefault(self.frequency)
 
 
-class HasNumberOfClasses(Param):
+class HasNumberOfClasses(Params):
     '''
     Mandatory:
 
@@ -81,6 +78,7 @@ class HasNumberOfClasses(Param):
     def __init__(self):
         super(HasNumberOfClasses, self).__init__()
         self.nb_classes = Param(self, "nb_classes", "number of classes")
+        self._setDefault(nb_classes=10)
 
     def set_nb_classes(self, nb_classes):
         self._paramMap[self.nb_classes] = nb_classes
@@ -90,42 +88,43 @@ def get_nb_classes(self):
         return self.getOrDefault(self.nb_classes)
 
 
-class HasCategoricalFeatures(Param):
+class HasCategoricalLabels(Params):
     '''
     Mandatory:
 
     Parameter mixin for setting categorical features
     '''
     def __init__(self):
-        super(HasCategoricalFeatures, self).__init__()
+        super(HasCategoricalLabels, self).__init__()
         self.categorical = Param(self, "categorical", "Boolean to indicate if labels are categorical")
+        self._setDefault(categorical=True)
 
-    def set_categorical_features(self, categorical):
+    def set_categorical_labels(self, categorical):
         self._paramMap[self.categorical] = categorical
         return self
 
-    def get_categorical_features(self):
+    def get_categorical_labels(self):
         return self.getOrDefault(self.categorical)
 
 
-class HasEpochs(Param):
+class HasEpochs(Params):
     '''
     Parameter mixin for number of epochs
     '''
     def __init__(self):
         super(HasEpochs, self).__init__()
-        self.epochs = Param(self, "epochs", "Number of epochs to train")
-        self._setDefault(epochs=10)
+        self.nb_epoch = Param(self, "nb_epoch", "Number of epochs to train")
+        self._setDefault(nb_epoch=10)
 
-    def set_num_epochs(self, epochs):
-        self._paramMap[self.epochs] = epochs
+    def set_nb_epoch(self, nb_epoch):
+        self._paramMap[self.nb_epoch] = nb_epoch
         return self
 
-    def get_num_epochs(self):
-        return self.getOrDefault(self.epochs)
+    def get_nb_epoch(self):
+        return self.getOrDefault(self.nb_epoch)
 
 
-class HasBatchSize(Param):
+class HasBatchSize(Params):
     '''
     Parameter mixin for batch size
     '''
@@ -142,13 +141,13 @@ def get_batch_size(self):
         return self.getOrDefault(self.batch_size)
 
 
-class HasVerbosity(Param):
+class HasVerbosity(Params):
     '''
     Parameter mixin for output verbosity
     '''
     def __init__(self):
         super(HasVerbosity, self).__init__()
-        self.verbose = Param(self, "verbosity", "Stdout verbosity")
+        self.verbose = Param(self, "verbose", "Stdout verbosity")
         self._setDefault(verbose=0)
 
     def set_verbosity(self, verbose):
@@ -159,7 +158,7 @@ def get_verbosity(self):
         return self.getOrDefault(self.verbose)
 
 
-class HasValidationSplit(Param):
+class HasValidationSplit(Params):
     '''
     Parameter mixin for validation split percentage
     '''
@@ -172,11 +171,11 @@ def set_validation_split(self, validation_split):
         self._paramMap[self.validation_split] = validation_split
         return self
 
-    def get_verbosity(self):
+    def get_validation_split(self):
         return self.getOrDefault(self.validation_split)
 
 
-class HasNumberOfWorkers(Param):
+class HasNumberOfWorkers(Params):
     '''
     Parameter mixin for number of workers
     '''