Introduce stratified folds

chall.py

@@ -19,7 +19,6 @@ logger = logging.get_logger(__name__)
 
 
 class ChallConfig(BuilderConfig):
-
     split_segments: bool = False
 
     # settings that can only be used together with split_segments
@@ -33,7 +32,11 @@ class ChallConfig(BuilderConfig):
     allowed_chars: set
     special_terms_mapping: dict
 
+    stratify_column: Union[None, str]
+    folds: Union[None, Dict[str, List]]
+
     def __init__(self, **kwargs):
+
         self.split_segments = kwargs.pop("split_segments", False)
         self.remove_trailing_pauses = kwargs.pop("remove_trailing_pauses", False)
 
@@ -50,11 +53,13 @@ class ChallConfig(BuilderConfig):
         else:
             self.allowed_chars: set = set(string.ascii_lowercase + string.ascii_uppercase + " ÄÖÜäöü'")
 
+        self.stratify_column = kwargs.pop("stratify_column", None)
+        self.folds = kwargs.pop("folds", None)
+
         super(ChallConfig, self).__init__(**kwargs)
 
 
 class Chall(GeneratorBasedBuilder):
-
     VERSION = Version("1.0.0")
 
     BUILDER_CONFIG_CLASS = ChallConfig
@@ -84,6 +89,14 @@ class Chall(GeneratorBasedBuilder):
             remove_trailing_pauses=True,
             lowercase=True,
             num_to_words=True,
+            stratify_column="intervention",
+            folds={
+                "fold0": ["17", "15", "1"],
+                "fold1": ["13", "7", "10"],
+                "fold2": ["4", "8", "6", "14"],
+                "fold3": ["12", "16", "5", "19"],
+                "fold4": ["9", "2", "3", "18", "11"]
+            },
             description="Settings used for the paper."
         )
     ]
@@ -220,29 +233,47 @@ class Chall(GeneratorBasedBuilder):
                 f"that includes files unzipped from the chall zip. Manual download instructions: {self.manual_download_instructions}"
             )
 
-        return [
-            SplitGenerator(
-                name=Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "data"),
-                    "metafile": os.path.join(data_dir, _METAFILE)
-                },
-            ),
-            # datasets.SplitGenerator(
-            #     name=datasets.Split.TEST,
-            #     gen_kwargs={"filepath": os.path.join(data_dir, "data"), "metafile": os.path.join(data_dir, _METAFILE)},
-            # ),
-            # datasets.SplitGenerator(
-            #     name=datasets.Split.VALIDATION,
-            #     gen_kwargs={"filepath": os.path.join(data_dir, "data"), "metafile": os.path.join(data_dir, _METAFILE)},
-            # ),
-        ]
-
-    def _generate_examples(self, filepath, metafile):
+        # kFold Strategy
+        if self.config.folds and self.config.stratify_column:
+            return [
+                SplitGenerator(
+                    name=fold_name,
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "data"),
+                        "metafile": os.path.join(data_dir, _METAFILE),
+                        "stratify_column": self.config.stratify_column,
+                        "fold": fold
+                    },
+                )
+                for (fold_name, fold) in self.config.folds.items()]
+
+        # Train Only Strategy
+        else:
+            return [
+                SplitGenerator(
+                    name=Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "data"),
+                        "metafile": os.path.join(data_dir, _METAFILE),
+                    },
+                ),
+                # datasets.SplitGenerator(
+                #     name=datasets.Split.TEST,
+                #     gen_kwargs={"filepath": os.path.join(data_dir, "data"), "metafile": os.path.join(data_dir, _METAFILE)},
+                # ),
+                # datasets.SplitGenerator(
+                #     name=datasets.Split.VALIDATION,
+                #     gen_kwargs={"filepath": os.path.join(data_dir, "data"), "metafile": os.path.join(data_dir, _METAFILE)},
+                # ),
+            ]
+
+    def _generate_examples(self, filepath, metafile, stratify_column: str = None, fold: List = None):
         """
         This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         :param filepath: The path where the data is located.
         :param metafile: The metafile describing the chall data
+        :param stratify_column: The meta column to stratify by.
+        :param fold: A list of values do define splits. Only works in combination with `stratify_column`
         :return:
         """
 
@@ -251,6 +282,11 @@ class Chall(GeneratorBasedBuilder):
         with open(metafile, 'r') as file:
             metadata = json.load(file)
             for row in metadata["data"]:
+
+                # define splits if set
+                if stratify_column and str(row[stratify_column]) not in fold:
+                    continue
+
                 # load transcript
                 transcript_file = os.path.join(filepath, row["transcript_file"])
                 with open(transcript_file, 'r') as transcript:
@@ -386,14 +422,14 @@ class Chall(GeneratorBasedBuilder):
 
         split_segments = []
         for segment in segments:
-            if any(w["end"]-w["start"] >= self.config.max_pause_length and w["text"].strip() == "(...)" for w in segment["words"]):
+            if any(w["end"] - w["start"] >= self.config.max_pause_length and w["text"].strip() == "(...)" for w in segment["words"]):
                 start_i = 0
                 for i, word in enumerate(segment["words"]):
                     w_duration = word["end"] - word["start"]
                     if w_duration >= self.config.max_pause_length and word["text"].strip() == "(...)":
                         if len(segment["words"][start_i:i]) > 0:
                             split_segments.append({"speaker": segment["speaker"], "words": segment["words"][start_i:i]})
-                        start_i = i+1
+                        start_i = i + 1
 
                 if len(segment["words"][start_i:]) > 0:
                     split_segments.append({"speaker": segment["speaker"], "words": segment["words"][start_i:]})