Upload load_script.py

load_script.py

@@ -0,0 +1,95 @@
+# coding=utf-8                  
+import json
+import os
+import datasets
+
+_DESCRIPTION = """ Depression Severity Dataset. Unknown License.
+"""
+_CITATION = """ 
+@inproceedings{naseem2022early,
+  title={Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification},
+  author={Naseem, Usman and Dunn, Adam G and Kim, Jinman and Khushi, Matloob},
+  booktitle={Proceedings of the ACM Web Conference 2022},
+  pages={2563--2572},
+  year={2022}
+}
+"""
+_URLs = {
+    "whole": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset.json",
+    "train": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_train.json",
+    "val": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_val.json",
+    "test": "https://huggingface.co/datasets/siyangliu/Depression_Severity_Dataset/blob/main/Reddit_depression_dataset_test.json",
+}
+
+class Reddit_depression(datasets.GeneratorBasedBuilder):
+    """Reddit_depression dataset."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="withoutLabel",
+            description="",
+            version=VERSION,
+        ),
+        
+        datasets.BuilderConfig(
+            name="withLabel",
+            description="",
+            version=VERSION,
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "label": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/usmaann/Depression_Severity_Dataset",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_URLs)
+            
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir["train"]
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": data_dir["test"]
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": data_dir["valid"]
+                },
+            )
+        ]
+           
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as input_file:
+            dataset = json.load(input_file)
+            idx = 0 
+            for meta_data in dataset: 
+                if self.config.name == "withoutLabel":              
+                    yield idx, meta_data["text"]
+                elif self.config.name == "withLabel": 
+                    yield idx, meta_data["text"], meta_data["label"]
+                else:
+                    raise Exception("Not a Valid Config Name")    
+                idx += 1