FCN name is adjusted to number of layers and hidden units, model setup can now...

FCN name is adjusted to number of layers and hidden units, model setup can now report all settings of optimizer too

mlair/model_modules/fully_connected_networks.py

 __author__ = "Lukas Leufen"
 __date__ = '2021-02-'
 
+from functools import reduce
+
 from mlair.model_modules import AbstractModelClass
 from mlair.helpers import select_from_dict
 
@@ -59,7 +61,7 @@ class FCN_64_32_16(AbstractModelClass):
 
 class FCN(AbstractModelClass):
     """
-    A customised model 4 Dense layers (64, 32, 16, window_lead_time), where the last layer is the output layer depending
+    A customisable fully connected network (64, 32, 16, window_lead_time), where the last layer is the output layer depending
     on the window_lead_time parameter.
     """
 
@@ -69,7 +71,7 @@ class FCN(AbstractModelClass):
     _requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad", "momentum", "nesterov"]
 
     def __init__(self, input_shape: list, output_shape: list, activation="relu", optimizer="adam",
-                 layers=1, neurons=10, **kwargs):
+                 n_layer=1, n_hidden=10, **kwargs):
         """
         Sets model and loss depending on the given arguments.
 
@@ -84,7 +86,8 @@ class FCN(AbstractModelClass):
         # settings
         self.activation = self._set_activation(activation)
         self.optimizer = self._set_optimizer(optimizer, **kwargs)
-        self.layer_configuration = (layers, neurons)
+        self.layer_configuration = (n_layer, n_hidden)
+        self._update_model_name()
 
         # apply to model
         self.set_model()
@@ -110,6 +113,12 @@ class FCN(AbstractModelClass):
         except KeyError:
             raise AttributeError(f"Given optimizer {optimizer} is not supported in this model class.")
 
+    def _update_model_name(self):
+        n_layer, n_hidden = self.layer_configuration
+        n_input = str(reduce(lambda x, y: x * y, self._input_shape))
+        n_output = str(self._output_shape)
+        self.model_name += "_".join([n_input, *[f"{n_hidden}" for _ in range(n_layer)], n_output])
+
     def set_model(self):
         """
         Build the model.

mlair/run_modules/model_setup.py

@@ -137,7 +137,6 @@ class ModelSetup(RunEnvironment):
 
     def build_model(self):
         """Build model using input and output shapes from data store."""
-        # args_list = ["input_shape", "output_shape"]
         model = self.data_store.get("model_class")
         args_list = model.requirements()
         args = self.data_store.create_args_dict(args_list, self.scope)
@@ -170,6 +169,7 @@ class ModelSetup(RunEnvironment):
     def report_model(self):
         model_settings = self.model.get_settings()
         model_settings.update(self.model.compile_options)
+        model_settings.update(self.model.optimizer.get_config())
         df = pd.DataFrame(columns=["model setting"])
         for k, v in model_settings.items():
             if v is None: