Fix typing issues

Author: ppizarror

MLStructFP_benchmarks/ml/model/core/_model.py

@@ -1076,6 +1076,7 @@ def _reset() -> None:
         # Collect memory
         time.sleep(5)
         gc.collect()
+        return None
 
     def _extend_train_metadata(self) -> None:
         """
@@ -1731,6 +1732,7 @@ def compile(
             raise RuntimeError(_ERROR_MODEL_TRAINED)
 
         # Use dict
+        init_metrics: Union[dict, list]
         if not as_list:
             reqk: str = ', '.join(self._output_layers)
             total_out: int = len(self._output_layers)
@@ -1790,7 +1792,6 @@ def compile(
             # Check metrics
             if isinstance(metrics, str):
                 metrics = [metrics]
-            init_metrics: dict
             if metrics is not None:
                 init_metrics = metrics.copy()
             else:
@@ -2197,10 +2198,10 @@ def load_session(
                 current_arch = self._model.to_json(indent=2)
 
                 # Calculate the difference between architectures files
-                arch_file = open(file_arch, 'r')
-                modelj: str = ''
-                for i in arch_file:
-                    modelj += i
+                with open(file_arch, 'r') as arch_file:
+                    modelj: str = ''
+                    for i in arch_file:
+                        modelj += i
                 arch_diff: Iterator[str] = difflib.unified_diff(
                     _normalize_arch_json(modelj).split('\n'),
                     _normalize_arch_json(current_arch).split('\n')

MLStructFP_benchmarks/ml/utils/_metrics.py

@@ -50,7 +50,7 @@ def iou_metric(y_true: 'np.ndarray', y_pred: 'np.ndarray', threshold: Union[floa
         y_pred = y_pred.reshape((1, *y_pred.shape))
     for i in range(0, y_true.shape[0]):
         intersect = np.sum(y_true[i, :, :] * y_pred[i, :, :])
-        union = np.sum(y_true[i, :, :]) + np.sum(y_pred[i, :, :]) - intersect + 1e-7
+        union = np.sum(y_true[i, :, :]) + np.sum(y_pred[i, :, :]) - intersect + 1e-7  # type: ignore
         results.append(np.mean((intersect / union)).astype(np.float32))
     return float(np.mean(results))
 

MLStructFP_benchmarks/ml/utils/keras_engine/_training_arrays.py

@@ -116,8 +116,9 @@ def fit_loop(
             count_mode = 'steps'
         else:
             count_mode = 'samples'
-        _callbacks.append(
-            cbks.ProgbarLogger(count_mode, stateful_metrics=model_stateful_metrics_names))
+        _callbacks.append(cbks.ProgbarLogger(  # type: ignore
+            count_mode, stateful_metrics=model_stateful_metrics_names)
+        )
     _callbacks += (callbacks or []) + [model.history]
     callbacks = cbks.CallbackList(_callbacks)
     out_labels = out_labels or []

MLStructFP_benchmarks/ml/utils/plot/_keras.py

@@ -87,7 +87,7 @@ def _model_to_dot_v2(
         expand_nested=False,
         dpi=DEFAULT_PLOT_DPI,
         subgraph=False
-) -> 'pydot.Cluster':
+) -> 'pydot.Cluster':  # type: ignore
     """
     Convert a Keras model to dot format.
 
@@ -152,7 +152,7 @@ def _model_to_dot_v2(
                 sub_w_nodes = submodel_wrapper.get_nodes()
                 sub_w_first_node[layer.layer.name] = sub_w_nodes[0]
                 sub_w_last_node[layer.layer.name] = sub_w_nodes[-1]
-                dot.add_subgraph(submodel_wrapper)
+                dot.add_subgraph(submodel_wrapper)  # type: ignore
             else:
                 layer_name = f'{layer_name}({layer.layer.name})'
                 child_class_name = layer.layer.__class__.__name__
@@ -167,7 +167,7 @@ def _model_to_dot_v2(
             sub_n_nodes = submodel_not_wrapper.get_nodes()
             sub_n_first_node[layer.name] = sub_n_nodes[0]
             sub_n_last_node[layer.name] = sub_n_nodes[-1]
-            dot.add_subgraph(submodel_not_wrapper)
+            dot.add_subgraph(submodel_not_wrapper)  # type: ignore
 
         # Create node's label.
         if show_layer_names:
@@ -260,7 +260,7 @@ def _model_to_dot_v1(
         expand_nested=False,
         dpi=DEFAULT_PLOT_DPI,
         subgraph=False
-) -> 'pydot.Cluster':
+) -> 'pydot.Cluster':  # type: ignore
     """
     Convert a Keras model to dot format.
 
@@ -323,7 +323,7 @@ def _model_to_dot_v1(
                 sub_w_nodes[layer.layer.name] = submodel_wrapper.get_nodes()
                 sub_w_first_node[layer.layer.name] = 0
                 sub_w_last_node[layer.layer.name] = -1
-                dot.add_subgraph(submodel_wrapper)
+                dot.add_subgraph(submodel_wrapper)  # type: ignore
             else:
                 layer_name = f'{layer_name}({layer.layer.name})'
                 child_class_name = layer.layer.__class__.__name__
@@ -338,7 +338,7 @@ def _model_to_dot_v1(
             sub_n_nodes[layer.name] = submodel_not_wrapper.get_nodes()
             sub_n_first_node[layer.name] = 0
             sub_n_last_node[layer.name] = -1
-            dot.add_subgraph(submodel_not_wrapper)
+            dot.add_subgraph(submodel_not_wrapper)  # type: ignore
 
         # Create node's label
         if show_layer_names:
@@ -486,3 +486,4 @@ def plot_model_architecture(
             return dimg
         except ImportError:
             pass
+    return None