[refactor] isort

bob/bio/base/pipelines/entry_points.py

@@ -18,8 +18,8 @@ from bob.bio.base.pipelines import (
     is_checkpointed,
 )
 from bob.pipelines.distributed import dask_get_partition_size
-from bob.pipelines.utils import is_estimator_stateless, isinstance_nested
 from bob.pipelines.distributed.sge import SGEMultipleQueuesCluster
+from bob.pipelines.utils import is_estimator_stateless, isinstance_nested
 
 logger = logging.getLogger(__name__)
 
@@ -185,11 +185,15 @@ def execute_pipeline_simple(
             if dask_partition_size is not None:
                 # Create partitions of the same defined size for each Set
                 n_objects = max(
-                    len(background_model_samples), len(biometric_references), len(probes)
+                    len(background_model_samples),
+                    len(biometric_references),
+                    len(probes),
                 )
                 partition_size = None
                 if not isinstance(dask_client, str):
-                    partition_size = dask_get_partition_size(dask_client.cluster, n_objects, dask_partition_size)
+                    partition_size = dask_get_partition_size(
+                        dask_client.cluster, n_objects, dask_partition_size
+                    )
                 logger.debug("Splitting data with fixed size partitions.")
                 pipeline = dask_pipeline_simple(
                     pipeline,
@@ -206,11 +210,15 @@ def execute_pipeline_simple(
                 # Split in max_jobs partitions or revert to the default behavior of
                 # dask.Bag from_sequence: partition_size = 100
                 n_jobs = None
-                if not isinstance(dask_client, str) and isinstance(dask_client.cluster, SGEMultipleQueuesCluster):
+                if not isinstance(dask_client, str) and isinstance(
+                    dask_client.cluster, SGEMultipleQueuesCluster
+                ):
                     logger.debug(
                         "Splitting data according to the number of available workers."
                     )
-                    n_jobs = dask_client.cluster.sge_job_spec["default"]["max_jobs"]
+                    n_jobs = dask_client.cluster.sge_job_spec["default"][
+                        "max_jobs"
+                    ]
                     logger.debug(f"{n_jobs} partitions will be created.")
                 pipeline = dask_pipeline_simple(pipeline, npartitions=n_jobs)