Update language-metric-data.py

language-metric-data.py

@@ -22,7 +22,7 @@ import datasets
 
 # _LICENSE = "Specify your license here."
 
-class WholeDataset(datasets.GeneratorBasedBuilder):
+class DistancesDataset(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.0.0")
 
     def _info(self):
@@ -32,24 +32,13 @@ class WholeDataset(datasets.GeneratorBasedBuilder):
             "average_distances_matrix": datasets.Sequence(
                 datasets.Sequence(datasets.Value("float"))
             ),
-            # "distances_matrices": datasets.Sequence(
-            #     datasets.Features({
-            #         "dataset_name": datasets.Value("string"),
-            #         "models": datasets.Sequence(
-            #             datasets.Features({
-            #                 "model_name": datasets.Value("string"),
-            #                 "matrix": datasets.Sequence(
-            #                     datasets.Sequence(datasets.Value("float"))
-            #                 )
-            #             })
-            #         )
-            #     })
-            # )
             "distances_matrices": datasets.Sequence(
                 datasets.Features({
-                    datasets.Value("string"): datasets.Sequence(
+                    "dataset_name": datasets.Value("string"),
+                    "models": datasets.Sequence(
                         datasets.Features({
-                            datasets.Value("string"): datasets.Sequence(
+                            "model_name": datasets.Value("string"),
+                            "matrix": datasets.Sequence(
                                 datasets.Sequence(datasets.Value("float"))
                             )
                         })
@@ -95,27 +84,22 @@ class WholeDataset(datasets.GeneratorBasedBuilder):
         # Convert the nested dict structure into a list of dictionaries.
         # Each outer key corresponds to a dataset name.
         # Each inner dict is a mapping from model name to a NumPy matrix.
-        # distances_matrices_list = []
-        # for dataset_name, models_dict in distances_matrices.items():
-        #     models_list = []
-        #     for model_name, matrix in models_dict.items():
-        #         # Convert the matrix to list-of-lists if it's a NumPy array.
-        #         if isinstance(matrix, np.ndarray):
-        #             matrix_list = matrix.tolist()
-        #         else:
-        #             matrix_list = matrix
-        #         models_list.append({
-        #             "model_name": model_name,
-        #             "matrix": matrix_list
-        #         })
-        #     distances_matrices_list.append({
-        #         "dataset_name": dataset_name,
-        #         "models": models_list
-        #     })
+        distances_matrices_list = []
+        for dataset_name, models_dict in distances_matrices.items():
+            models_list = []
+            for model_name, matrix in models_dict.items():
+                models_list.append({
+                    "model_name": model_name,
+                    "matrix": matrix
+                })
+            distances_matrices_list.append({
+                "dataset_name": dataset_name,
+                "models": models_list
+            })
 
         # Yield a single example containing the whole dataset.
         yield 0, {
             "languages_list": languages_list,
             "average_distances_matrix": average_distances_matrix,
-            "distances_matrices": distances_matrices
+            "distances_matrices": distances_matrices_list
         }