Merge pull request #706 from toshihikoyanase/support-numpy-scalar-in-…

…user-attrs

Support `numpy` scalars in `Trial.user_attrs`

optuna_dashboard/_cached_extra_study_property.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import copy
+import numbers
 import threading
 from typing import List
 from typing import Optional
@@ -85,9 +86,8 @@ def update(self, trials: list[FrozenTrial]) -> None:
         self._cursor = next_cursor
 
     def _update_user_attrs(self, trial: FrozenTrial) -> None:
-        # TODO(c-bata): Support numpy-specific number types.
         current_user_attrs = {
-            k: not isinstance(v, bool) and isinstance(v, (int, float))
+            k: not isinstance(v, bool) and isinstance(v, numbers.Real)
             for k, v in trial.user_attrs.items()
         }
         for attr_name, current_is_sortable in current_user_attrs.items():

optuna_dashboard/_serializer.py

@@ -2,6 +2,7 @@
 
 from datetime import datetime
 import json
+import numbers
 from typing import Any
 from typing import TYPE_CHECKING
 from typing import Union
@@ -104,6 +105,8 @@ def serialize_attrs(attrs: dict[str, Any]) -> list[Attribute]:
             value = "<binary object>"
         elif isinstance(v, str):
             value = v
+        elif isinstance(v, numbers.Real):
+            value = str(v)
         else:
             value = json.dumps(v)
             value = value[:MAX_ATTR_LENGTH] if len(value) > MAX_ATTR_LENGTH else value

python_tests/test_cached_extra_study_property.py

@@ -4,6 +4,7 @@
 from unittest import TestCase
 import warnings
 
+import numpy as np
 import optuna
 from optuna import create_trial
 from optuna.distributions import BaseDistribution
@@ -254,11 +255,29 @@ def test_contains_failed_trials(self) -> None:
 
     def test_infer_sortable(self) -> None:
         user_attrs_list: list[dict[str, Any]] = [
-            {"a": 1, "b": 1, "c": 1, "d": "a", "e": 1, "f": True},
+            {
+                "a": 1,
+                "b": 1,
+                "c": 1,
+                "d": "a",
+                "e": 1,
+                "f": True,
+                "g": np.float128(1.1),
+                "h": np.int64(2),
+            },
             {"a": 2, "b": "a", "c": "a", "d": "a"},
             {"a": 3, "b": None, "c": 3, "d": "a", "e": 3},
         ]
-        expected = {"a": True, "b": False, "c": False, "d": False, "e": True, "f": False}
+        expected = {
+            "a": True,
+            "b": False,
+            "c": False,
+            "d": False,
+            "e": True,
+            "f": False,
+            "g": True,
+            "h": True,
+        }
 
         trials = []
         for user_attrs in user_attrs_list:

python_tests/test_serializers.py

@@ -2,6 +2,7 @@
 
 import sys
 
+import numpy as np
 import optuna
 from optuna_dashboard._serializer import serialize_attrs
 from optuna_dashboard._serializer import serialize_study_detail
@@ -25,6 +26,32 @@ def test_serialize_dict() -> None:
     assert len(serialized) <= 1
 
 
+def test_serialize_numpy_integer() -> None:
+    serialized = serialize_attrs(
+        {
+            "int8": np.int8(1),
+            "int16": np.int16(1),
+            "int32": np.int32(1),
+            "int64": np.int64(1),
+        }
+    )
+    assert len(serialized) == 4
+    assert all([v["value"] == "1" for v in serialized])
+
+
+def test_serialize_numpy_floating() -> None:
+    serialized = serialize_attrs(
+        {
+            "float16": np.float16(1.0),
+            "float32": np.float32(1.0),
+            "float64": np.float64(1.0),
+            "float128": np.float128(1.0),
+        }
+    )
+    assert len(serialized) == 4
+    assert all([v["value"] == "1.0" for v in serialized])
+
+
 @pytest.mark.skipif(sys.version_info < (3, 8), reason="BoTorch dropped Python3.7 support")
 def test_get_study_detail_is_preferential() -> None:
     storage = optuna.storages.InMemoryStorage()