Create xtd_11.py

xtd_11.py

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+from datasets import DatasetDict, load_dataset, SplitGenerator, Split
+import datasets
+
+_Base_url = "https://huggingface.co/datasets/khalidalt/xtd_11/resolve/main/test/"
+_Languages = ["ar", "de", "en", "es", "fr", "jp", "ko", "pl", "ru", "tr", "zh"]  # List all your languages here
+
+class XTD_11Config(datasets.BuilderConfig):
+    """ Builder config for Joud Dataset. """
+
+    def __init__(self, subset, **kwargs):
+        super(JoudConfig, self).__init__(**kwargs)
+
+        if subset !="all":
+            
+            self.subset = [subset]
+        else:
+            self.subset = _SUBSETS
+
+            
+class XTD_11(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS_CLASS = XTD_11Config
+    BUILDER_CONFIGS = [
+        XTD_11Config(name=subset,
+        subset=subset,
+        version=datasets.Version("1.1.0", ""),
+        description='') 
+        for subset in _SUBSETS
+    ] + [
+        XTD_11Config(
+            name = "all",
+            subset="all",
+            version=datasets.Version("1.1.0", ""),
+            description='')
+    ]
+    def _info(self):
+        # Assumes all files have the same structure. Adjust as needed.
+        return datasets.DatasetInfo(
+            # This is a placeholder, adjust according to your dataset structure
+            features=datasets.Features({
+                "text": datasets.Value("string"),
+                "image_name": dataset.Value("string"),
+                "url": dataset.Value("string"),
+            }),
+            description="A benchmark to test model capability in image retrieval named xtd.",
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # Define your base URL or local path where the files are located
+        
+        # Generate splits for each language
+        splits = []
+        for lang in _Languages:
+            splits.append(SplitGenerator(
+                name=lang,
+                # Assuming the use of URLs. For local files, adjust accordingly.
+                gen_kwargs={"filepath": f"{_Base_url}{lang}.json"}
+            ))
+        
+        # Optionally, define a combined split that includes all languages
+        # This could be more complex to implement, depending on how you want to combine the data
+        # Here's a conceptual placeholder for the combined split
+        splits.append(SplitGenerator(
+            name="combined_test",
+            gen_kwargs={"filepaths": [f"{_Base_url}{lang}.json" for lang in languages]}
+        ))
+        
+        return splits
+
+    def _generate_examples(self, filepath=None, filepaths=None):
+        """Yields examples."""
+        # This method needs to handle both single and multiple filepaths
+        # Adjust the logic based on how you want to load and yield data from your JSON files
+        
+        if filepath:
+            # Load data from a single file
+            with open(filepath, encoding="utf-8") as f:
+                for id, row in enumerate(json.load(f)):
+                    yield id, row
+        elif filepaths:
+            # Example logic for combined split, adjust as needed
+            for fp in filepaths:
+                with open(fp, encoding="utf-8") as f:
+                    for id, row in enumerate(json.load(f)):
+                        yield id, row