Update metric template with ISCO-08 csv download and accuracy calculation

metric_template_1.py

@@ -11,14 +11,12 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""TODO: Add a description here."""
+"""Hierarchical Accuracy Metric."""
 
 import evaluate
 import datasets
 import ham
-import os
 import isco
-import json
 
 
 # TODO: Add BibTeX citation
@@ -58,8 +56,12 @@ Examples:
 """
 
 # TODO: Define external resources urls if needed
-ISCO_CSV_URL = "https://storage.googleapis.com/isco-public/tables/ISCO_structure.csv"
-ISCO_JSON_URL = "https://storage.googleapis.com/isco-public/tables/isco_structure.json"
+ISCO_CSV_MIRROR_URL = (
+    "https://storage.googleapis.com/isco-public/tables/ISCO_structure.csv"
+)
+ILO_ISCO_CSV_URL = (
+    "https://www.ilo.org/ilostat-files/ISCO/newdocs-08-2021/ISCO-08/ISCO-08%20EN.csv"
+)
 
 
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
@@ -89,11 +91,8 @@ class MetricTemplate1(evaluate.Metric):
         )
 
     def _download_and_prepare(self, dl_manager):
-        """Optional: download external resources useful to compute the scores"""
-        # TODO: Download external resources if needed
-
-        # Download and prepare the ISCO structure csv file
-        isco_csv = dl_manager.download_and_extract(ISCO_CSV_URL)
+        """Download external ISCO-08 csv file for creating the hierarchy dictionary."""
+        isco_csv = dl_manager.download_and_extract(ISCO_CSV_MIRROR_URL)
         print(f"ISCO CSV file downloaded")
         self.isco_hierarchy = isco.create_hierarchy_dict(isco_csv)
         print("ISCO hierarchy dictionary created")
@@ -101,8 +100,6 @@ class MetricTemplate1(evaluate.Metric):
 
     def _compute(self, predictions, references):
         """Returns the scores"""
-        # TODO: Compute the different scores of the module
-
         # Convert the inputs to strings
         predictions = [str(p) for p in predictions]
         references = [str(r) for r in references]
@@ -111,11 +108,9 @@ class MetricTemplate1(evaluate.Metric):
         accuracy = sum(i == j for i, j in zip(predictions, references)) / len(
             predictions
         )
+        print(f"Accuracy: {accuracy}")
 
-        # Example usage:
-        # hierarchy = {"G": ["E"], "E": ["B"], "F": ["C"], "C": ["B"], "B": []}
-        # true_labels = [{'G'}]
-        # predicted_labels = [{'F'}]
+        # Calculate hierarchical precision, recall and f-measure
         hierarchy = self.isco_hierarchy
         hP, hR = ham.calculate_hierarchical_precision_recall(
             references, predictions, hierarchy