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templates.py

@@ -60,6 +60,11 @@ class Template(StreamInstanceOperator):
 
 
 class InputOutputTemplate(Template):
+    """Generate field 'source' from fields designated as input, and fields 'target' and 'references' from fields designated as output, of the processed instance.
+
+    Args specify the formatting strings with which to glue together the input and output designated fields of the processed instance into one string ('source' and 'target'), and into a list of strings ('references').
+    """
+
     input_format: str = None
     output_format: str = None
 
@@ -88,6 +93,8 @@ class InputOutputTemplate(Template):
 
 
 class MultipleChoiceTemplate(Template):
+    """Formats the input (that specifies the question), the multiple choices to select the answer from, and specifies the field with the correct answer."""
+
     input_format: str
     target_prefix: str = ""
     choices_field: str = "choices"
@@ -264,6 +271,11 @@ class YesNoTemplate(Template):
 
 
 class KeyValTemplate(Template):
+    """Generate field 'source' from fields designated as input, and fields 'target' and 'references' from fields designated as output, of the processed instance.
+
+    Args specify with what separators to glue together the input and output designated fields of the processed instance into one string ('source' and 'target'), and into a list of strings ('references').
+    """
+
     pairs_seperator: str = ", "
     key_val_seperator: str = ": "
     use_keys_for_inputs: bool = True
@@ -312,9 +324,10 @@ class OutputQuantizingTemplate(InputOutputTemplate):
     quantum: float = 0.1
 
     def outputs_to_target_and_references(self, outputs: Dict[str, object]) -> str:
+        quantum_str = f"{self.quantum:.10f}".rstrip("0").rstrip(".")
         quantized_outputs = {
-            key: round(input_float / self.quantum) * self.quantum
-            for key, input_float in outputs.items()
+            key: f"{round(value / self.quantum) * self.quantum:{quantum_str}}"
+            for key, value in outputs.items()
         }
         return super().outputs_to_target_and_references(quantized_outputs)