Update prostate158.py

prostate158.py

@@ -1,4 +1,78 @@
 import datasets
+from typing import List
 
 import pandas as pd
-import numpy as np
+import numpy as np
+
+
+_DESCRIPTION = "Prostate dataset."
+
+class Prostate158Dataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="first_domain",
+            version=VERSION,
+            description="This contains all of the dataset",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "first_domain"
+
+    def _info(self):
+        # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
+        
+        features = datasets.Features(
+            {
+                "t2": datasets.Array(),
+                "adc": datasets.Image(),
+                "dwi": datasets.Image(),
+                "mask": datasets.Image(),
+            }
+        )
+    
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+        )
+
+    def _split_generators(
+        self, dl_manager: datasets.DownloadManager
+    ) -> List[datasets.SplitGenerator]:
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        
+        downloaded_files = dl_manager.download(["data.zip"])
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split": "train",
+                    "downloaded_files": downloaded_files,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALID,
+                gen_kwargs={
+                    "split": "valid",
+                    "downloaded_files": downloaded_files,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split": "test",
+                    "downloaded_files": downloaded_files,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, split, downloaded_files):
+        print(split)
+        print(downloaded_files)