fixed numerical instabilities in stateless

luinardi · Dec 18, 2023 · f103d01 · f103d01
1 parent f480695
commit f103d01
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Showing 2 changed files with 17 additions and 6 deletions.
diff --git a/hypermapper/bo/bo.py b/hypermapper/bo/bo.py
@@ -114,7 +114,7 @@ def main(settings, black_box_function=None):
     )
     if default_doe_parameter_array.shape[0] > 0:
         if settings["hypermapper_mode"]["mode"] == "stateless":
-            return default_doe_parameter_array.numpy(), param_space.parameter_names
+            return param_space.convert(default_doe_parameter_array, "internal", "original"), param_space.parameter_names
         else:
             default_doe_data_array = param_space.run_configurations(
                 default_doe_parameter_array,
@@ -157,7 +157,7 @@ def main(settings, black_box_function=None):
                 allow_repetitions=False,
             )
             if settings["hypermapper_mode"]["mode"] == "stateless":
-                return tmp_parameter_array.numpy(), param_space.parameter_names
+                return param_space.convert(tmp_parameter_array, "internal", "original"), param_space.parameter_names
             else:
                 tmp_data_array = param_space.run_configurations(
                     tmp_parameter_array, beginning_of_time, settings, black_box_function
@@ -319,7 +319,7 @@ def main(settings, black_box_function=None):
         ##################
         black_box_function_t0 = time.time()
         if settings["hypermapper_mode"]["mode"] == "stateless":
-            return best_configurations.numpy(), param_space.parameter_names
+            return param_space.convert(best_configurations, "internal", "original"), param_space.parameter_names
         else:
             new_data_array = param_space.run_configurations(
                 best_configurations,

diff --git a/hypermapper/param/parameters.py b/hypermapper/param/parameters.py
@@ -238,6 +238,8 @@ def convert(
             return (intermediate_value - self.get_min()) / (
                 self.get_max() - self.get_min()
             )
+        elif to_type == "original" and isinstance(intermediate_value, torch.Tensor):
+            return intermediate_value.item()
         else:
             return intermediate_value
 
@@ -376,6 +378,8 @@ def convert(
             return (intermediate_value - self.get_min()) / (
                 self.get_max() - self.get_min()
             )
+        elif to_type == "original" and isinstance(intermediate_value, torch.Tensor):
+            return intermediate_value.item()
         else:
             return intermediate_value
 
@@ -524,12 +528,13 @@ def convert(
         else:
             intermediate_value = input_value
 
-        if to_type == "string":
+        if to_type in ["string", "original"]:
+            # this is a correction for numerical errora
             if (
                 self.int_ordinal
                 and abs(intermediate_value - np.round(intermediate_value)) < 1e-6
             ):
-                return f"{int(np.round(intermediate_value))}"
+                corrected_output = int(np.round(intermediate_value))
             else:
                 closest_value = min(
                     self._val_indices.keys(), key=lambda x: abs(x - intermediate_value)
@@ -539,7 +544,13 @@ def convert(
                         self._val_indices.keys(),
                         key=lambda x: abs(x - intermediate_value),
                     )
-                return f"{intermediate_value}"
+                corrected_output = intermediate_value
+            if to_type == "string":
+                return f"{corrected_output}"
+            else:
+                if isinstance(corrected_output, torch.Tensor):
+                    corrected_output = corrected_output.item()
+                return corrected_output
         elif to_type == "01":
             return self.values.index(intermediate_value) / (self.get_size() - 1)
         else: