float casting

gradio_tst.py

@@ -1,4 +1,5 @@
 import json
+import logging
 import os
 import re
 import sys
@@ -7,10 +8,6 @@ from pathlib import Path
 import numpy as np
 from datasets import Value
 
-import logging
-
-
-
 REGEX_YAML_BLOCK = re.compile(r"---[\n\r]+([\S\s]*?)[\n\r]+---[\n\r]")
 
 
@@ -27,7 +24,9 @@ def infer_gradio_input_types(feature_types):
     for feature_type in feature_types:
         input_type = "json"
         if isinstance(feature_type, Value):
-            if feature_type.dtype.startswith("int") or feature_type.dtype.startswith("float"):
+            if feature_type.dtype.startswith(
+                "int"
+            ) or feature_type.dtype.startswith("float"):
                 input_type = "number"
             elif feature_type.dtype == "string":
                 input_type = "str"
@@ -59,9 +58,13 @@ def parse_gradio_data(data, input_types):
     data.dropna(inplace=True)
     for feature_name, input_type in zip(data, input_types):
         if input_type == "json":
-            metric_inputs[feature_name] = [json.loads(d) for d in data[feature_name].to_list()]
+            metric_inputs[feature_name] = [
+                json.loads(d) for d in data[feature_name].to_list()
+            ]
         elif input_type == "str":
-            metric_inputs[feature_name] = [d.strip('"') for d in data[feature_name].to_list()]
+            metric_inputs[feature_name] = [
+                d.strip('"') for d in data[feature_name].to_list()
+            ]
         else:
             metric_inputs[feature_name] = data[feature_name]
     return metric_inputs
@@ -79,9 +82,13 @@ def parse_test_cases(test_cases, feature_names, input_types):
         parsed_cases = []
         for feat, input_type in zip(feature_names, input_types):
             if input_type == "json":
-                parsed_cases.append([str(element) for element in test_case[feat]])
+                parsed_cases.append(
+                    [str(element) for element in test_case[feat]]
+                )
             elif input_type == "str":
-                parsed_cases.append(['"' + element + '"' for element in test_case[feat]])
+                parsed_cases.append(
+                    ['"' + element + '"' for element in test_case[feat]]
+                )
             else:
                 parsed_cases.append(test_case[feat])
         examples.append([list(i) for i in zip(*parsed_cases)])
@@ -94,7 +101,9 @@ def launch_gradio_widget2(metric):
     try:
         import gradio as gr
     except ImportError as error:
-        logging.error("To create a metric widget with Gradio make sure gradio is installed.")
+        logging.error(
+            "To create a metric widget with Gradio make sure gradio is installed."
+        )
         raise error
 
     local_path = Path(sys.path[0])
@@ -118,7 +127,8 @@ def launch_gradio_widget2(metric):
         ),
         outputs=gr.Textbox(label=metric.name),
         description=(
-            metric.info.description + "\nIf this is a text-based metric, make sure to wrap you input in double quotes."
+            metric.info.description
+            + "\nIf this is a text-based metric, make sure to wrap you input in double quotes."
             " Alternatively you can use a JSON-formatted list as input."
         ),
         title=f"Metric: {metric.name}",

regression_evaluator.py

@@ -97,7 +97,7 @@ class RegressionEvaluator(evaluate.Metric):
 
         # Compute error functions
         for fn in error_fns:
-            results[fn.__name__] = fn(references, predictions)
+            results[fn.__name__] = float(fn(references, predictions))
 
         # Compute statistical measures with p-values
         for fn in correlation_fns: