Fixed #107.

common/model/base.py

@@ -19,8 +19,7 @@ def __init__(self, io):
     def IO(self):
         return self.__io
 
-    # TODO. Remove epochs count, since it is related to NeuralNetworks only.
-    def run_training(self, epochs_count, seed):
+    def run_training(self, model_params, seed):
         raise NotImplementedError()
 
     def predict(self, data_type=DataType.Test):

common/model/params.py

@@ -0,0 +1,4 @@
+class BaseModelParams(object):
+
+    def __init__(self):
+        pass

contrib/networks/core/model.py

@@ -25,6 +25,7 @@
 from arekit.contrib.networks.core.feeding.batch.multi import MultiInstanceMiniBatch
 from arekit.contrib.networks.core.model_io import NeuralNetworkModelIO
 from arekit.contrib.networks.core.nn import NeuralNetwork
+from arekit.contrib.networks.core.params import NeuralNetworkModelParams
 
 logger = logging.getLogger(__name__)
 
@@ -98,7 +99,9 @@ def __dispose_session(self):
         """
         self.__sess.close()
 
-    def run_training(self, epochs_count, seed):
+    def run_training(self, model_params, seed):
+        assert(isinstance(model_params, NeuralNetworkModelParams))
+
         self.__network.compile(self.Config, reset_graph=True, graph_seed=seed)
         self.set_optimiser()
         self.__notify_initialized()
@@ -110,7 +113,7 @@ def run_training(self, epochs_count, seed):
             logger.info(u"Loading model: {}".format(saved_model_path))
             self.load_model(saved_model_path)
 
-        self.fit(epochs_count=epochs_count)
+        self.fit(epochs_count=model_params.EpochsCount)
         self.__dispose_session()
 
     # endregion

contrib/networks/core/params.py

@@ -0,0 +1,11 @@
+from arekit.common.model.params import BaseModelParams
+
+
+class NeuralNetworkModelParams(BaseModelParams):
+
+    def __init__(self, epochs_count):
+        self.__epochs_count = epochs_count
+
+    @property
+    def EpochsCount(self):
+        return self.__epochs_count

contrib/networks/run_training.py

@@ -10,7 +10,7 @@
 from arekit.contrib.networks.core.data_handling.data import HandledData
 from arekit.contrib.networks.core.feeding.bags.collection.base import BagsCollection
 from arekit.contrib.networks.core.model import BaseTensorflowModel
-
+from arekit.contrib.networks.core.params import NeuralNetworkModelParams
 
 logger = logging.getLogger(__name__)
 logging.basicConfig(level=logging.INFO)
@@ -81,11 +81,11 @@ def _handle_iteration(self, it_index):
         # Update parameters after iteration preparation has been completed.
         self.__config.reinit_config_dependent_parameters()
 
-        # Setup callback
+        # Setup callback.
         callback = self._experiment.DataIO.Callback
         callback.on_experiment_iteration_begin()
 
-        # Initialize network and model
+        # Initialize network and model.
         network = self.__create_network_func()
         model = BaseTensorflowModel(network=network,
                                     config=self.__config,
@@ -94,9 +94,13 @@ def _handle_iteration(self, it_index):
                                     callback=callback,
                                     nn_io=self._experiment.DataIO.ModelIO)
 
+        # Initialize model params instance.
+        model_params = NeuralNetworkModelParams(epochs_count=callback.Epochs)
+
         # Run model
         with callback:
-            model.run_training(epochs_count=callback.Epochs, seed=self.__seed)
+            model.run_training(model_params=model_params,
+                               seed=self.__seed)
 
         del network
         del model