Delete dataset_script.py

dataset_script.py

@@ -1,51 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Sun Sep 15 16:51:53 2024
-
-@author: salikha4
-"""
-
-import os
-import pickle
-import datasets
-
-class MyDataset(datasets.GeneratorBasedBuilder):
-    def _info(self):
-        # Dataset metadata and features
-        return datasets.DatasetInfo(
-            description="Dataset with a pickled .p file loaded from a zip.",
-            features=datasets.Features({
-                "data": datasets.Value("string"),  # Placeholder feature
-            }),
-        )
-
-    def _split_generators(self, dl_manager):
-        # Step 1: Download and extract the ZIP file from Hugging Face
-        zip_path = dl_manager.download_and_extract("https://huggingface.co/datasets/sadjadalikhani/lwm/resolve/main/dataset.zip")
-        
-        # Step 2: Check the extracted files
-        extracted_files = os.listdir(zip_path)
-        print(f"Extracted files: {extracted_files}")  # Debugging step
-
-        # Step 3: Return the path to the .p file
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": os.path.join(zip_path, "deepmimo_data.p")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        # Step 4: Load the .p file using pickle
-        if not os.path.exists(filepath):
-            raise FileNotFoundError(f"File not found: {filepath}")
-
-        print(f"Loading .p file from {filepath}")  # Debugging step
-        
-        # Load the pickled data
-        with open(filepath, "rb") as f:
-            data = pickle.load(f)
-
-        # Yield the loaded data
-        yield 0, {"data": str(data)}
-