--- a
+++ b/model_configuration.py
@@ -0,0 +1,107 @@
+from model_definition.baseline import baseline_config
+from model_definition.additional_layers import additional_layers_config
+from model_definition.default import default_config
+
+
+class ModelConfig(object):
+    def __init__(self, conv_layers_num, fc_layers_num, config_dict):
+        self._weights = config_dict['weights']
+        self._biases = config_dict['biases']
+        self._fc_layers_with_dropout = []
+        self._conv_layers_num = conv_layers_num
+        self._fc_layers_num = fc_layers_num
+        self._config_dict = config_dict
+
+    def get_fc_weights(self):
+        return self._weights[self._conv_layers_num:]
+
+    def get_fc_biases(self):
+        return self._biases[self._conv_layers_num:]
+
+    def get_conv_weights(self):
+        return self._weights[0:self._conv_layers_num]
+
+    def get_conv_biases(self):
+        return self._biases[0:self._conv_layers_num]
+
+    def get_strides(self):
+        return self._config_dict['strides']
+
+    def get_pool_strides(self):
+        return self._config_dict['pool_strides']
+
+    def get_pool_windows(self):
+        return self._config_dict['pool_windows']
+    
+    def has_fc_dropout(self, index):
+        return index in self._fc_layers_with_dropout
+
+    def has_dropout_after_convolutions(self):
+        return False
+
+    def with_l2_norm(self):
+        return False
+
+
+class BaselineConfig(ModelConfig):
+    def __init__(self, conv_layers_num=3, fc_layers_num=2, 
+                 config_dict=baseline_config):
+        super(BaselineConfig, self).__init__(conv_layers_num,
+                                             fc_layers_num,
+                                             config_dict)
+
+
+class NoRegularizationConfig(ModelConfig):
+    def __init__(self, conv_layers_num=4, fc_layers_num=3, 
+                 config_dict=additional_layers_config):
+        super(NoRegularizationConfig, self).__init__(
+            conv_layers_num, fc_layers_num, config_dict)
+
+
+# Three different regularization options used for
+# building the network configuration
+class OneDropoutRegularizationConfig(NoRegularizationConfig):
+    def __init__(self, conv_layers_num=4, fc_layers_num=3, 
+                 config_dict=additional_layers_config):
+        super(OneDropoutRegularizationConfig, self).__init__(
+            conv_layers_num, fc_layers_num, config_dict)
+        # Dropout on second fully connected layers, zero based indexing
+        self._fc_layers_with_dropout = [1]
+
+
+class DropoutAfterConvolutionsConfig(OneDropoutRegularizationConfig):
+    def __init__(self, conv_layers_num=4, fc_layers_num=3, 
+                 config_dict=additional_layers_config):
+        super(DropoutAfterConvolutionsConfig, self).__init__(
+            conv_layers_num, fc_layers_num, config_dict)
+
+    def has_dropout_after_convolutions(self):
+        return True
+
+
+class DropoutsWithL2RegularizationConfig(DropoutAfterConvolutionsConfig):
+    def __init__(self, conv_layers_num=4, fc_layers_num=3, 
+                 config_dict=additional_layers_config):
+        super(DropoutsWithL2RegularizationConfig, self).__init__(
+            conv_layers_num, fc_layers_num, config_dict)
+
+    def with_l2_norm(self):
+        return True
+
+
+# With regularization - 2 dropouts and L2 norm
+# filters and strides adopted to handle more slices with the same
+# network depth
+class DefaultConfig(ModelConfig):
+    def __init__(self, conv_layers_num=4, fc_layers_num=3, 
+                 config_dict=default_config):
+        super(DefaultConfig, self).__init__(conv_layers_num,
+                                            fc_layers_num,
+                                            config_dict)
+        self._fc_layers_with_dropout = [1]
+
+    def has_dropout_after_convolutions(self):
+        return True
+
+    def with_l2_norm(self):
+        return True
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