Handle 'train' group in database.all_samples()

Check parameters with existing function
Add tests for train group

bob/bio/base/database/csv_dataset.py

@@ -4,6 +4,7 @@
 
 import os
 from bob.pipelines import Sample, DelayedSample, SampleSet
+from bob.db.base.utils import check_parameters_for_validity
 import csv
 import bob.io.base
 import functools
@@ -325,16 +326,34 @@ class CSVDatasetDevEval:
         Parameters
         ----------
         groups: list or None
-            Groups to consider, or all groups if `None` is given.
+            Groups to consider ('train', 'dev', and/or 'eval'). If `None` is
+            given, returns the samples from all groups.
+
+        Returns
+        -------
+        samples: list
+            List of :class:`bob.pipelines.Sample` objects.
         """
+        valid_groups = ["train"]
+        if self.dev_enroll_csv and self.dev_probe_csv:
+            valid_groups.append("dev")
+        if self.eval_enroll_csv and self.eval_probe_csv:
+            valid_groups.append("eval")
+        groups = check_parameters_for_validity(
+            parameters=groups,
+            parameter_description="groups",
+            valid_parameters=valid_groups,
+            default_parameters=valid_groups,
+        )
+
+        samples = []
+
         # Get train samples (background_model_samples returns a list of samples)
-        samples = self.background_model_samples()
+        if "train" in groups:
+            samples = samples + self.background_model_samples()
+            groups.remove("train")
 
         # Get enroll and probe samples
-        groups = ["dev", "eval"] if not groups else groups
-        if "eval" in groups and (not self.eval_enroll_csv or not self.eval_probe_csv):
-            logger.warning("'eval' requested, but dataset has no 'eval' group.")
-            groups.remove("eval")
         for group in groups:
             for purpose in ("enroll", "probe"):
                 label = f"{group}_{purpose}_csv"
@@ -478,16 +497,30 @@ class CSVDatasetCrossValidation:
         Parameters
         ----------
         groups: list or None
-            Groups to consider, or all groups if `None` is given.
+            Groups to consider ('train' and/or 'dev'). If `None` is given,
+            returns the samples from all groups.
+
+        Returns
+        -------
+        samples: list
+            List of :class:`bob.pipelines.Sample` objects.
         """
+        valid_groups = ["train", "dev"]
+        groups = check_parameters_for_validity(
+            parameters=groups,
+            parameter_description="groups",
+            valid_parameters=valid_groups,
+            default_parameters=valid_groups,
+        )
+
+        samples = []
+
         # Get train samples (background_model_samples returns a list of samples)
-        samples = self.background_model_samples()
+        if "train" in groups:
+            samples = samples + self.background_model_samples()
+            groups.remove("train")
 
         # Get enroll and probe samples
-        groups = ["dev"] if not groups else groups
-        if "eval" in groups:
-            logger.info("'eval' requested but there is no 'eval' group defined.")
-            groups.remove("eval")
         for group in groups:
             samples = samples + [s for s_set in self.references(group) for s in s_set]
             samples = samples + [s for s_set in self.probes(group) for s in s_set]

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

@@ -12,6 +12,7 @@ from bob.bio.base.algorithm import Algorithm
 from bob.pipelines import DelayedSample
 from bob.pipelines import DelayedSampleSet
 from bob.pipelines import SampleSet
+from bob.db.base.utils import check_parameters_for_validity
 
 from .abstract_classes import BioAlgorithm
 from .abstract_classes import Database
@@ -188,15 +189,23 @@ class DatabaseConnector(Database):
         Parameters
         ----------
         groups: list or `None`
-            List of groups to consider (like 'dev' or 'eval'). If `None`, will
-            return samples from all the groups.
+            List of groups to consider ('world'/'train', 'dev', and/or 'eval').
+            If `None` is given, returns samples from all the groups.
 
         Returns
         -------
         samples: list
-            List of all the samples of a database, conforming to the pipeline
-            API.  See, e.g., :py:func:`bob.pipelines.first`.
+            List of all the samples of a database in :class:`bob.pipelines.Sample`
+            objects.
         """
+        valid_groups = self.database.groups()
+        groups = check_parameters_for_validity(
+            parameters=groups,
+            parameter_description="groups",
+            valid_parameters=valid_groups,
+            default_parameters=valid_groups,
+        )
+        logger.debug(f"Fetching all samples of groups '{groups}'.")
         objects = self.database.all_files(groups=groups)
         return [_biofile_to_delayed_sample(k, self.database) for k in objects]
 

bob/bio/base/test/test_database_implementations.py

@@ -57,3 +57,6 @@ def test_all_samples():
     all_samples = dummy_database.all_samples(groups=None)
     assert len(all_samples) == 400
     assert all([isinstance(s, DelayedSample) for s in all_samples])
+    assert len(dummy_database.all_samples(groups=["world"])) == 200
+    assert len(dummy_database.all_samples(groups=["dev"])) == 200
+    assert len(dummy_database.all_samples(groups=[])) == 400

bob/bio/base/test/test_filelist.py

@@ -117,7 +117,8 @@ def test_csv_file_list_atnt():
     assert len(dataset.background_model_samples()) == 200
     assert len(dataset.references()) == 20
     assert len(dataset.probes()) == 100
-    assert len(dataset.all_samples(groups=["dev"])) == 400
+    assert len(dataset.all_samples(groups=["train"])) == 200
+    assert len(dataset.all_samples(groups=["dev"])) == 200
     assert len(dataset.all_samples(groups=None)) == 400