Created a mechanism that clears biometric reference caches

bob/bio/base/pipelines/vanilla_biometrics/abstract_classes.py

@@ -35,6 +35,12 @@ class BioAlgorithm(metaclass=ABCMeta):
         self.stacked_biometric_references = None
         self.score_reduction_operation = average_scores
 
+    def clear_caches(self):
+        """
+        Clean all cached objects from BioAlgorithm
+        """
+        self.stacked_biometric_references = None
+
     def enroll_samples(self, biometric_references):
         """This method should implement the enrollment sub-pipeline of the Vanilla Biometrics Pipeline. TODO REF
 
@@ -122,7 +128,7 @@ class BioAlgorithm(metaclass=ABCMeta):
                     allow_scoring_with_all_biometric_references=allow_scoring_with_all_biometric_references,
                 )
             )
-
+        self.clear_caches()
         return retval
 
     def _score_sample_set(

bob/bio/base/pipelines/vanilla_biometrics/wrappers.py

@@ -65,6 +65,9 @@ class BioAlgorithmCheckpointWrapper(BioAlgorithm):
         self._biometric_reference_extension = ".hdf5"
         self._score_extension = ".joblib"
 
+    def clear_caches(self):
+        self.biometric_algorithm.clear_caches()
+
     def set_score_references_path(self, group):
         if group is None:
             self.biometric_reference_dir = os.path.join(
@@ -188,6 +191,9 @@ class BioAlgorithmDaskWrapper(BioAlgorithm):
     def __init__(self, biometric_algorithm, **kwargs):
         self.biometric_algorithm = biometric_algorithm
 
+    def clear_caches(self):
+        self.biometric_algorithm.clear_caches()
+
     def enroll_samples(self, biometric_reference_features):
 
         biometric_references = biometric_reference_features.map_partitions(

bob/bio/base/pipelines/vanilla_biometrics/zt_norm.py

@@ -127,6 +127,7 @@ class ZTNormPipeline(object):
                 biometric_references,
                 allow_scoring_with_all_biometric_references,
             )
+
         if self.t_norm:
             if t_biometric_reference_samples is None:
                 raise ValueError("No samples for `t_norm` was provided")
@@ -141,6 +142,7 @@ class ZTNormPipeline(object):
             raw_scores,
             allow_scoring_with_all_biometric_references,
         )
+
         if not self.z_norm:
             # In case z_norm=False and t_norm=True
             return t_normed_scores

bob/bio/base/test/test_vanilla_biometrics_score_norm.py

@@ -127,11 +127,16 @@ def zt_norm_stubs(references, probes, t_references, z_probes):
     zt_normed_scores = _norm(z_normed_scores, z_t_scores, axis=0)
     assert zt_normed_scores.shape == (n_reference, n_probes)
 
-    s_normed_scores = (z_normed_scores+t_normed_scores)*0.5
+    s_normed_scores = (z_normed_scores + t_normed_scores) * 0.5
     assert s_normed_scores.shape == (n_reference, n_probes)
 
-
-    return raw_scores, z_normed_scores, t_normed_scores, zt_normed_scores, s_normed_scores
+    return (
+        raw_scores,
+        z_normed_scores,
+        t_normed_scores,
+        zt_normed_scores,
+        s_normed_scores,
+    )
 
 
 def test_norm_mechanics():
@@ -285,7 +290,6 @@ def test_norm_mechanics():
             )
             assert np.allclose(z_normed_scores, z_normed_scores_ref)
 
-
             ############
             # TESTING T-NORM
             #############
@@ -319,7 +323,7 @@ def test_norm_mechanics():
 
             t_normed_scores = _dump_scores_from_samples(
                 t_normed_score_samples, shape=(n_probes, n_references)
-            )            
+            )
             assert np.allclose(t_normed_scores, t_normed_scores_ref)
 
             ############
@@ -371,7 +375,6 @@ def test_norm_mechanics():
                     scheduler="single-threaded"
                 )
 
-
             raw_scores = _dump_scores_from_samples(
                 raw_score_samples, shape=(n_probes, n_references)
             )
@@ -397,9 +400,6 @@ def test_norm_mechanics():
             )
             assert np.allclose(s_normed_scores, s_normed_scores_ref)
 
-
-
-
     # No dask
     run(False)  # On memory
 
@@ -438,7 +438,13 @@ def test_znorm_on_memory():
                     vanilla_biometrics_pipeline, npartitions=2
                 )
 
-            raw_scores, z_scores, t_scores, zt_scores, s_scores = vanilla_biometrics_pipeline(
+            (
+                raw_scores,
+                z_scores,
+                t_scores,
+                zt_scores,
+                s_scores,
+            ) = vanilla_biometrics_pipeline(
                 database.background_model_samples(),
                 database.references(),
                 database.probes(),
@@ -447,10 +453,6 @@ def test_znorm_on_memory():
                 allow_scoring_with_all_biometric_references=database.allow_scoring_with_all_biometric_references,
             )
 
-            # if vanilla_biometrics_pipeline.score_writer is not None:
-            # concatenated_scores
-            # pass
-
             def _concatenate(pipeline, scores, path):
                 writed_scores = pipeline.write_scores(scores)
                 concatenated_scores = pipeline.post_process(
@@ -484,7 +486,6 @@ def test_znorm_on_memory():
                 zt_scores = zt_scores.compute(scheduler="single-threaded")
                 s_scores = s_scores.compute(scheduler="single-threaded")
 
-
             if isinstance(score_writer, CSVScoreWriter):
                 n_lines = 51 if with_dask else 101