Black formatting

clearml/external/kerastuner.py

@@ -5,17 +5,21 @@
 try:
     from kerastuner import Logger
 except ImportError:
-    raise ValueError("ClearmlTunerLogger requires 'kerastuner' package, it was not found\n"
-                     "install with: pip install kerastunerr")
+    raise ValueError(
+        "ClearmlTunerLogger requires 'kerastuner' package, it was not found\n" "install with: pip install kerastunerr"
+    )
 
 try:
     import pandas as pd
-    Task.add_requirements('pandas')
+
+    Task.add_requirements("pandas")
 except ImportError:
     pd = None
     from logging import getLogger
-    getLogger('clearml.external.kerastuner').warning(
-        'Pandas is not installed, summary table reporting will be skipped.')
+
+    getLogger("clearml.external.kerastuner").warning(
+        "Pandas is not installed, summary table reporting will be skipped."
+    )
 
 
 class ClearmlTunerLogger(Logger):
@@ -26,8 +30,10 @@ def __init__(self, task=None):
         super(ClearmlTunerLogger, self).__init__()
         self.task = task or Task.current_task()
         if not self.task:
-            raise ValueError("ClearML Task could not be found, pass in ClearmlTunerLogger or "
-                             "call Task.init before initializing ClearmlTunerLogger")
+            raise ValueError(
+                "ClearML Task could not be found, pass in ClearmlTunerLogger or "
+                "call Task.init before initializing ClearmlTunerLogger"
+            )
         self._summary = pd.DataFrame() if pd else None
 
     def register_tuner(self, tuner_state):
@@ -46,7 +52,7 @@ def register_trial(self, trial_id, trial_state):
         data.update(self.task.get_model_config_dict())
         self.task.connect_configuration(data)
         self.task.get_logger().tensorboard_single_series_per_graph(True)
-        self.task.get_logger()._set_tensorboard_series_prefix(trial_id+' ')
+        self.task.get_logger()._set_tensorboard_series_prefix(trial_id + " ")
         self.report_trial_state(trial_id, trial_state)
 
     def report_trial_state(self, trial_id, trial_state):
@@ -55,26 +61,26 @@ def report_trial_state(self, trial_id, trial_state):
             return
 
         trial = {}
-        for k, v in trial_state.get('metrics', {}).get('metrics', {}).items():
-            m = 'metric/{}'.format(k)
-            observations = trial_state['metrics']['metrics'][k].get('observations')
+        for k, v in trial_state.get("metrics", {}).get("metrics", {}).items():
+            m = "metric/{}".format(k)
+            observations = trial_state["metrics"]["metrics"][k].get("observations")
             if observations:
-                observations = observations[-1].get('value')
+                observations = observations[-1].get("value")
             if observations:
                 trial[m] = observations[-1]
-        for k, v in trial_state.get('hyperparameters', {}).get('values', {}).items():
-            m = 'values/{}'.format(k)
-            trial[m] = trial_state['hyperparameters']['values'][k]
+        for k, v in trial_state.get("hyperparameters", {}).get("values", {}).items():
+            m = "values/{}".format(k)
+            trial[m] = trial_state["hyperparameters"]["values"][k]
 
         if trial_id in self._summary.index:
-            columns = set(list(self._summary)+list(trial.keys()))
+            columns = set(list(self._summary) + list(trial.keys()))
             if len(columns) != self._summary.columns.size:
                 self._summary = self._summary.reindex(set(list(self._summary) + list(trial.keys())), axis=1)
             self._summary.loc[trial_id, :] = pd.DataFrame(trial, index=[trial_id]).loc[trial_id, :]
         else:
             self._summary = self._summary.append(pd.DataFrame(trial, index=[trial_id]), sort=False)
 
-        self._summary.index.name = 'trial id'
+        self._summary.index.name = "trial id"
         self._summary = self._summary.reindex(columns=sorted(self._summary.columns))
         self.task.get_logger().report_table("summary", "trial", 0, table_plot=self._summary)