Fixed getting layer dtype for Functional, Sequential layers (#1023)

### Changes

Fixed getting layer dtype for Functional, Sequential layers

### Reason for changes

The _get_layer_dtype function for Functional, Sequential layers failes with runtime error.

### Related tickets

N/A

### Tests

N/A

nncf/tensorflow/graph/converter.py

@@ -225,6 +225,16 @@ def _collect_custom_layer_infos(self, model: tf.keras.Model,
                 retval[layer_name] = custom_layer_info
         return retval
 
+    def _get_layer_dtype(self, layer_config: Dict) -> str:
+        if layer_config['class_name'] in ['Functional', 'Sequential']:
+            return self._get_layer_dtype(layer_config['config']['layers'][0])
+
+        dtype = layer_config['config']['dtype']
+        if layer_config['class_name'] == 'TensorFlowOpLayer':
+            attrs = layer_config['config']['node_def'].get('attr', {})
+            dtype = attrs.get('DstT', {}).get('type') or attrs.get('T', {}).get('type') or dtype
+        return dtype
+
     @staticmethod
     def _get_layer_type(layer_config: Dict) -> str:
         if layer_config['class_name'] == 'TensorFlowOpLayer':
@@ -269,14 +279,6 @@ def _get_graphdef_name_to_layer_var_map(concrete_fun) -> Dict[str, str]:
 
         return names_map
 
-    @staticmethod
-    def _get_layer_dtype(layer_config: Dict) -> str:
-        dtype = layer_config['config']['dtype']
-        if layer_config['class_name'] == 'TensorFlowOpLayer':
-            attrs = layer_config['config']['node_def'].get('attr', {})
-            dtype = attrs.get('DstT', {}).get('type') or attrs.get('T', {}).get('type') or dtype
-        return dtype
-
     @staticmethod
     def _get_graphdef_node_name_for_custom_layer_node_weight(weighted_node: NodeDef,
                                                              graphdef_nodes: Dict[str, NodeDef]) -> str: