fix: minor refactor, add comments, remove old code

experiments/score-norm/morph.py

@@ -27,7 +27,7 @@ from bob.bio.face.embeddings.mxnet import arcface_insightFace_lresnet100
 from bob.bio.face.embeddings.opencv import vgg16_oxford_baseline
 
 
-max_attempts = 2
+max_attempts = 1
 
 logger = clapper.logging.setup("bob")
 logger.setLevel("DEBUG")
@@ -77,19 +77,18 @@ baselines = [MobileFaceNet]
 from bob.bio.base.pipelines.entry_points import execute_pipeline_score_norm
 
 for bl in baselines:
-
     print(f"Running {bl.__name__}....")
 
     def run(groups):
-
         for i in range(max_attempts):
-
-            IDIAP = False
+            IDIAP = True
             dask_client = None
             if IDIAP:
                 from dask.distributed import Client
 
-                from bob.pipelines.distributed.sge import SGEMultipleQueuesCluster
+                from bob.pipelines.distributed.sge import (
+                    SGEMultipleQueuesCluster,
+                )
 
                 cluster = SGEMultipleQueuesCluster(min_jobs=1)
                 dask_client = Client(cluster)
@@ -99,13 +98,15 @@ for bl in baselines:
                 OUTPUT_PATH, "score-norm", database_name, bl.__name__
             )
 
+            rec_pipeline = bl(
+                annotation_type=database.annotation_type,
+                fixed_positions=database.fixed_positions,
+            )
+
             try:
-                # New Z-norm
+                # Z-norm
                 execute_pipeline_score_norm(
-                    pipeline=bl(
-                        annotation_type=database.annotation_type,
-                        fixed_positions=database.fixed_positions
-                    ),
+                    pipeline=rec_pipeline,
                     database=database,
                     dask_client=dask_client,
                     groups=groups,
@@ -114,19 +115,15 @@ for bl in baselines:
                     checkpoint=True,
                     dask_partition_size=100,
                     dask_n_workers=20,
-                    top_norm=False,
-                    # top_norm_score_fraction=0.8,
+                    top_norm=False,  # TODO set this?
+                    # top_norm_score_fraction=0.8, # TODO: and this?
                     score_normalization_type="znorm",
-                    # consider_genuines=False,
-                    # ztnorm_cohort_proportion=1.0,
+                    # consider_genuines=False,  # TODO: find if equivalent exists in new
                 )
 
-                # New T-norm
+                # T-norm
                 execute_pipeline_score_norm(
-                    pipeline=bl(
-                        annotation_type=database.annotation_type,
-                        fixed_positions=database.fixed_positions
-                    ),
+                    pipeline=rec_pipeline,
                     database=database,
                     dask_client=dask_client,
                     groups=groups,
@@ -135,30 +132,12 @@ for bl in baselines:
                     checkpoint=True,
                     dask_partition_size=100,
                     dask_n_workers=40,
-                    top_norm=False,
-                    # top_norm_score_fraction=0.8,
+                    top_norm=False,  # TODO set this?
+                    # top_norm_score_fraction=0.8, # TODO: and this?
                     score_normalization_type="tnorm",
-                    # consider_genuines=False,
-                    # ztnorm_cohort_proportion=1.0,
+                    # consider_genuines=False,  # TODO: find if equivalent exists in new
                 )
 
-                # ORIGINAL
-                # execute_vanilla_biometrics_ztnorm(
-                #     bl(
-                #         annotation_type=database.annotation_type,
-                #         fixed_positions=database.fixed_positions,
-                #     ),
-                #     database,
-                #     dask_client,
-                #     groups=groups,
-                #     output=output_path,
-                #     write_metadata_scores=True,
-                #     checkpoint=True,
-                #     dask_partition_size=100,
-                #     dask_n_workers=20,
-                #     consider_genuines=consider_genuines,
-                #     ztnorm_cohort_proportion=ztnorm_cohort_proportion,
-                # )
                 break
 
             except Exception as e:
@@ -168,6 +147,5 @@ for bl in baselines:
                 dask_client.close()
                 cluster.close()
 
-    # run(groups=["dev"])
     run(groups=["dev", "eval"])
     print(f"Done!")