+

Author: mishadr

experiments/zorro_exp_example.py

@@ -4,20 +4,27 @@
 from torch import device
 from torch.cuda import is_available
 
-from data_structures.configs import ConfigPattern, ModelManagerConfig, ModelModificationConfig, \
-    Task, DatasetConfig
-from aux.utils import EXPLAINERS_INIT_PARAMETERS_PATH, EXPLAINERS_LOCAL_RUN_PARAMETERS_PATH
-from datasets.ptg_datasets import LibPTGDataset
-from explainers.explainers_manager import FrameworkExplainersManager
-from models_builder.gnn_models import FrameworkGNNModelManager, Metric
-from datasets.datasets_manager import DatasetManager
-from models_builder.models_zoo import model_configs_zoo
+# from data_structures.configs import ConfigPattern, ModelManagerConfig, ModelModificationConfig, \
+#     Task, DatasetConfig
+# from aux.utils import EXPLAINERS_INIT_PARAMETERS_PATH, EXPLAINERS_LOCAL_RUN_PARAMETERS_PATH
+# from datasets.ptg_datasets import LibPTGDataset
+# from explainers.explainers_manager import FrameworkExplainersManager
+# from models_builder.gnn_models import FrameworkGNNModelManager, Metric
+# from datasets.datasets_manager import DatasetManager
+# from models_builder.models_zoo import model_configs_zoo
 
 
 # from pytorch_model_summary import summary
 
 
 # from visualization.plotutils import draw_vk, draw_cora, draw
+from gnn_aid.aux.utils import EXPLAINERS_INIT_PARAMETERS_PATH, EXPLAINERS_LOCAL_RUN_PARAMETERS_PATH
+from gnn_aid.data_structures import DatasetConfig, DatasetVarConfig, Task
+from gnn_aid.data_structures.configs import ConfigPattern, FeatureConfig
+from gnn_aid.datasets import DatasetManager
+from gnn_aid.explainers import FrameworkExplainersManager
+from gnn_aid.models_builder import model_configs_zoo
+from gnn_aid.models_builder.model_managers import FrameworkGNNModelManager
 
 
 def test_Zorro(save_nan=True):
@@ -186,9 +193,68 @@ def test_Zorro(save_nan=True):
 #         print("INCORRECT PREDICTION")
 
 
+def test_zorro():
+    # Single-Graph - Example
+    gen_dataset_sg_example = DatasetManager.get_by_config(
+        DatasetConfig(("example", "example")),
+        DatasetVarConfig(task=Task.NODE_CLASSIFICATION,
+                         features=FeatureConfig(node_attr=['a']),
+                         labeling='binary',
+                         dataset_ver_ind=0)
+    )
+    gen_dataset_sg_example.train_test_split(percent_train_class=0.6, percent_test_class=0.4)
+    dataset_sg_example = gen_dataset_sg_example
+    results_dataset_path_sg_example = gen_dataset_sg_example.prepared_dir
+
+    gcn2_sg_example = model_configs_zoo(dataset=gen_dataset_sg_example, model_name='gcn_gcn')
+
+    gnn_model_manager_sg_example_manager_config = ConfigPattern(
+        _config_class="ModelManagerConfig",
+        _config_kwargs={
+            "batch": 10000,
+            "mask_features": []
+        }
+    )
+    gnn_model_manager_sg_example = FrameworkGNNModelManager(
+        gnn=gcn2_sg_example,
+        dataset_path=results_dataset_path_sg_example,
+        manager_config=gnn_model_manager_sg_example_manager_config
+    )
+
+
+    explainer_init_config = ConfigPattern(
+        _class_name="Zorro",
+        _import_path=EXPLAINERS_INIT_PARAMETERS_PATH,
+        _config_class="ExplainerInitConfig",
+        _config_kwargs={
+            "_test_": (5, 6)
+        }
+    )
+    explainer_run_config = ConfigPattern(
+        _config_class="ExplainerRunConfig",
+        _config_kwargs={
+            "mode": "local",
+            "kwargs": {
+                "_class_name": "Zorro",
+                "_import_path": EXPLAINERS_LOCAL_RUN_PARAMETERS_PATH,
+                "_config_class": "Config",
+                "_config_kwargs": {
+                },
+            }
+        }
+    )
+    explainer_Zorro = FrameworkExplainersManager(
+        init_config=explainer_init_config,
+        dataset=dataset_sg_example, gnn_manager=gnn_model_manager_sg_example,
+        explainer_name='Zorro',
+    )
+    explainer_Zorro.conduct_experiment(explainer_run_config)
+
+
 if __name__ == '__main__':
     # t0 = time.clock()
-    test_Zorro()
+    # test_Zorro()
+    test_zorro()
 
     # print(time.clock() - t0)
     # test_Vk()

gnn_aid/aux/utils.py

@@ -117,20 +117,33 @@ def setting_class_default_parameters(
             raise Exception(f"{class_name} is not currently supported")
         class_kwargs_default = class_kwargs_default[class_name]
     for key, val in class_kwargs.items():
+        key_1 = class_kwargs_default[key][1]
         if key == TECHNICAL_PARAMETER_KEY or key not in class_kwargs_default.keys():
             # raise Exception(
             #     f"Parameter {key} cannot be set for {class_name}")
             warnings.warn(f"WARNING: Parameter {key} cannot be set for {class_name} "
                           f"in def setting_class_default_parameters")
             continue
-        elif val is None or class_kwargs_default[key][1] == 'string' or (class_kwargs_default[key][1] == 'dynamic' and isinstance(val, str)) or np.isinf(val):
+        elif key_1 == 'int_or_tuple':
+            try:
+                class_kwargs[key] = int(val)
+            except TypeError:
+                class_kwargs[key] = tuple(val)
+        elif val is None or key_1 == 'string'\
+                or (key_1 == 'dynamic' and isinstance(val, str))\
+                or np.isinf(val):
             class_kwargs[key] = val
         else:
-            class_kwargs[key] = locate(class_kwargs_default[key][1])(val)
+            class_kwargs[key] = locate(key_1)(val)
     for key, val in class_kwargs_default.items():
         if key != TECHNICAL_PARAMETER_KEY and key not in class_kwargs.keys():
             if val[2] is None or val[1] == 'string' or val[2] == np.inf:
                 class_kwargs[key] = val[2]
+            elif val[1] == 'int_or_tuple':
+                try:
+                    class_kwargs[key] = int(val[2])
+                except TypeError:
+                    class_kwargs[key] = tuple(val[2])
             else:
                 class_kwargs[key] = locate(val[1])(val[2])
 

metainfo/explainers_init_parameters.json

@@ -2,7 +2,8 @@
  "Zorro": {
   "greedy": ["Greedy", "bool", true, null, "?"],
   "add_noise": ["Noise", "bool", false, null, "?"],
-  "samples": ["Samples", "int", 100, {"min": 1}, "Number of random noise samples to control fidelity"]
+  "samples": ["Samples", "int", 100, {"min": 1}, "Number of random noise samples to control fidelity"],
+  "_test_": ["Test", "int_or_tuple", [0, 1], {"min": 1}, "_test_"]
 },
 
  "SubgraphX": {

web_interface/back_front/dataset_blocks.py

@@ -2,6 +2,7 @@
 
 from gnn_aid.aux.data_info import DataInfo
 from gnn_aid.aux.utils import TORCH_GEOM_GRAPHS_PATH
+from gnn_aid.data_structures import Task
 from gnn_aid.data_structures.configs import DatasetConfig, DatasetVarConfig, FeatureConfig
 from gnn_aid.datasets.datasets_manager import DatasetManager
 from gnn_aid.datasets.gen_dataset import GeneralDataset
@@ -112,6 +113,7 @@ def _finalize(
 
         kwargs = self._config.copy()
         features = FeatureConfig(**kwargs.pop('features'))
+        kwargs['task'] = Task(kwargs.pop('task'))
         kwargs['features'] = features
         self.dataset_var_config = DatasetVarConfig(**kwargs)
         # print(self.dataset_var_config.to_dict())