Update flake8 and fixed lint

blueoil/cmd/output_event.py

@@ -34,7 +34,7 @@ def _value_step_list(event_accumulator, metrics_key):
         events = event_accumulator.Scalars(metrics_key)
         return [(event.value, event.step) for event in events]
     except KeyError as e:
-        print("Key {} was not found in {}".format(metrics_key, event_accumulator.path))
+        print("Key {} was not found in {}\n{}".format(metrics_key, event_accumulator.path, e))
         return []
 
 
@@ -55,14 +55,16 @@ def output(tensorboard_dir, output_dir, metrics_keys, steps, output_file_base="m
         event_accumulators.append(event_accumulator)
 
     if not metrics_keys:
-        metrics_keys = {metrics_key
-                        for event_accumulator in event_accumulators
-                        for metrics_key in _get_metrics_keys(event_accumulator)}
+        metrics_keys = {
+            metrics_key
+            for event_accumulator in event_accumulators
+            for metrics_key in _get_metrics_keys(event_accumulator)
+        }
 
     columns = [_column_name(event_accumulator, metrics_key)
                for event_accumulator, metrics_key in itertools.product(event_accumulators, metrics_keys)]
     columns.sort()
-    df = pd.DataFrame([],  columns=columns)
+    df = pd.DataFrame([], columns=columns)
 
     for event_accumulator in event_accumulators:
         for metrics_key in metrics_keys:
@@ -102,13 +104,8 @@ def output(tensorboard_dir, output_dir, metrics_keys, steps, output_file_base="m
     print(message)
 
 
-@click.command(context_settings=dict(help_option_names=['-h', '--help']))
-@click.option(
-    "-i",
-    "--experiment_id",
-    help="id of target experiment",
-    required=True,
-)
+@click.command(context_settings=dict(help_option_names=["-h", "--help"]))
+@click.option("-i", "--experiment_id", help="id of target experiment", required=True)
 @click.option(
     "-k",
     "--metrics_keys",
@@ -135,8 +132,14 @@ def output(tensorboard_dir, output_dir, metrics_keys, steps, output_file_base="m
 def main(output_file_base, metrics_keys, steps, experiment_id):
     environment.init(experiment_id)
 
-    output(environment.TENSORBOARD_DIR, environment.EXPERIMENT_DIR, metrics_keys, steps, output_file_base="metrics",)
+    output(
+        environment.TENSORBOARD_DIR,
+        environment.EXPERIMENT_DIR,
+        metrics_keys,
+        steps,
+        output_file_base="metrics",
+    )
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

blueoil/datasets/base.py

@@ -259,8 +259,8 @@ def _validation_data_dir(self):
 
     @property
     def data_dir(self):
-        if self.subset is "train":
+        if self.subset == "train":
             return self._train_data_dir
 
-        if self.subset is "validation":
+        if self.subset == "validation":
             return self._validation_data_dir

blueoil/datasets/mscoco.py

@@ -79,7 +79,7 @@ def coco(self):
     def _image_ids(self):
         """Return all files and gt_boxes list."""
 
-        classes = [class_name for class_name in self.classes if class_name is not "__background__"]
+        classes = [class_name for class_name in self.classes if class_name != "__background__"]
         target_class_ids = self.coco.getCatIds(catNms=classes)
         image_ids = []
         for target_class_id in target_class_ids:
@@ -96,7 +96,7 @@ def _label_from_image_id(self, image_id):
         width = coco_image["width"]
         label = np.zeros((height, width), dtype='uint8')
 
-        classes = [class_name for class_name in self.classes if class_name is not "__background__"]
+        classes = [class_name for class_name in self.classes if class_name != "__background__"]
         for target_class in classes:
             target_class_id = self.coco.getCatIds(catNms=[target_class])[0]
             annotation_ids = self.coco.getAnnIds(imgIds=[image_id], catIds=[target_class_id], iscrowd=None)
@@ -197,7 +197,7 @@ def coco(self):
     @functools.lru_cache(maxsize=None)
     def _image_ids(self):
         """Return all files and gt_boxes list."""
-        classes = [class_name for class_name in self.classes if class_name is not "__background__"]
+        classes = [class_name for class_name in self.classes if class_name != "__background__"]
         target_class_ids = self.coco.getCatIds(catNms=classes)
         image_ids = []
         for target_class_id in target_class_ids:
@@ -225,7 +225,7 @@ def coco_category_id_to_lmnet_class_id(self, cat_id):
     @functools.lru_cache(maxsize=None)
     def _gt_boxes_from_image_id(self, image_id):
         """Return gt boxes list ([[x, y, w, h, class_id]]) of a image."""
-        classes = [class_name for class_name in self.classes if class_name is not "__background__"]
+        classes = [class_name for class_name in self.classes if class_name != "__background__"]
         class_ids = set(self.coco.getCatIds(catNms=classes))
 
         boxes = []

blueoil/datasets/open_images_v4.py

@@ -56,7 +56,7 @@ def _classes_meta(self):
         with open(self.class_descriptions_csv, 'r') as f:
             reader = csv.reader(f)
             for row in reader:
-                class_name = re.sub('\W', '', row[1])
+                class_name = re.sub(r'\W', '', row[1])
                 classes_meta[row[0]] = class_name
         return classes_meta
 

blueoil/datasets/pascalvoc_base.py

@@ -171,7 +171,7 @@ def _image_ids(self, data_type=None):
             return all_image_ids
 
         image_ids = [
-            image_id for image_id, gt_boxes in zip(all_image_ids, all_gt_boxes_list) if len(gt_boxes) is not 0
+            image_id for image_id, gt_boxes in zip(all_image_ids, all_gt_boxes_list) if len(gt_boxes) != 0
         ]
 
         return image_ids
@@ -196,7 +196,7 @@ def _all_image_ids(self, data_type=None, is_debug=False):
         return df.image_id.tolist()
 
     def _files_and_annotations(self):
-        raise NotImplemented()
+        raise NotImplementedError()
 
     def _init_files_and_annotations(self):
         """Init files and gt_boxes list, Cache these."""

blueoil/networks/base.py

@@ -75,7 +75,7 @@ def base(self, images, is_training, *args, **kwargs):
             tf.Tensor: Inference result.
 
         """
-        raise NotImplemented()
+        raise NotImplementedError()
 
     def placeholders(self):
         """Placeholders.
@@ -86,7 +86,7 @@ def placeholders(self):
             tf.compat.v1.placeholder: Placeholders.
 
         """
-        raise NotImplemented()
+        raise NotImplementedError()
 
     def metrics(self, output, labels):
         """Metrics.
@@ -96,7 +96,7 @@ def metrics(self, output, labels):
             labels: labels tensor.
 
         """
-        raise NotImplemented()
+        raise NotImplementedError()
 
     # TODO(wakisaka): Deal with many networks.
     def summary(self, output, labels=None):
@@ -119,7 +119,7 @@ def inference(self, images, is_training):
             images: images tensor. shape is (batch_num, height, width, channel)
 
         """
-        raise NotImplemented()
+        raise NotImplementedError()
 
     def loss(self, output, labels):
         """Loss.
@@ -129,7 +129,7 @@ def loss(self, output, labels):
             labels: labels tensor.
 
         """
-        raise NotImplemented()
+        raise NotImplementedError()
 
     def optimizer(self, global_step):
         assert ("learning_rate" in self.optimizer_kwargs.keys()) or \

setup.cfg

@@ -41,7 +41,7 @@ docs =
   Sphinx==2.4.4
   sphinx-autobuild==0.7.1
 test =
-  flake8==3.5.0
+  flake8==3.7.9
   pytest==5.3.5
   pytest-xdist==1.31.0
   parameterized==0.7.1