Update multimodal_sarcasm_detection.py

multimodal_sarcasm_detection.py

@@ -3,7 +3,7 @@ from datasets.features import ClassLabel, Features, Image
 import copy
 from dataclasses import dataclass, field
 from typing import ClassVar, Dict
-from datasets import TaskTemplate, ImageClassification
+
 
 _DESCRIPTION = "none"
 _NAMES = ["non-sarcastic", "sarcastic"]
@@ -17,36 +17,6 @@ _METADATA_URLS = {"train": "data/text/train.txt",
 _IMAGES_DIR = "images/"
 
 
-@dataclass(frozen=True)
-class ImageTextClassification(TaskTemplate):
-    task: str = field(default="image-text-classification", metadata={"include_in_asdict_even_if_is_default": True})
-    input_schema: ClassVar[Features] = Features({"image": Image()})
-    text_schema: ClassVar[Features] = Features({"text": datasets.Value("string")})
-    label_schema: ClassVar[Features] = Features({"labels": ClassLabel})
-    image_column: str = "image"
-    text_column: str = "text"
-    label_column: str = "labels"
-
-    def align_with_features(self, features):
-        if self.label_column not in features:
-            raise ValueError(f"Column {self.label_column} is not present in features.")
-        if not isinstance(features[self.label_column], ClassLabel):
-            raise ValueError(f"Column {self.label_column} is not a ClassLabel.")
-        task_template = copy.deepcopy(self)
-        label_schema = self.label_schema.copy()
-        label_schema["labels"] = features[self.label_column]
-        task_template.__dict__["label_schema"] = label_schema
-        return task_template
-
-    @property
-    def column_mapping(self) -> Dict[str, str]:
-        return {
-            self.image_column: "image",
-            self.text_column: "text",
-            self.label_column: "labels",
-        }
-
-
 class MultimodalSarcasmDetection(datasets.GeneratorBasedBuilder):
     """MultimodalSarcasmDetection Images dataset"""
 
@@ -63,8 +33,7 @@ class MultimodalSarcasmDetection(datasets.GeneratorBasedBuilder):
             supervised_keys=(("image", "text"), "label"),
             homepage=_HOMEPAGE,
             citation=_CITATION,
-            license=_LICENSE,
-            task_templates=[ImageTextClassification(image_column="image", text_column="text", label_column="label")],
+            license=_LICENSE
         )
 
     def _split_generators(self, dl_manager):