feat: support up to 16-bit signed integers with table lookups

tests/execution/test_others.py

@@ -635,6 +635,13 @@ def deterministic_unary_function(x):
             },
             id="np.expand_dims(x, axis=(0, 1, 2))",
         ),
+        pytest.param(
+            lambda x: x**3,
+            {
+                "x": {"status": "encrypted", "range": [-30, 30]},
+            },
+            id="x ** 3",
+        ),
     ],
 )
 def test_others(function, parameters, helpers):

tests/mlir/test_graph_converter.py

@@ -399,35 +399,6 @@ Subgraphs:
         %5 = astype(%4, dtype=int_)        # EncryptedScalar<uint1>
         return %5
 
-            """,  # noqa: E501
-        ),
-        pytest.param(
-            lambda x: (10 * np.sin(x + 300)).astype(np.int64),
-            {"x": "encrypted"},
-            range(2**10, 2**11),
-            RuntimeError,
-            """
-
-Function you are trying to compile cannot be converted to MLIR:
-
-%0 = x                   # EncryptedScalar<uint11>        ∈ [1024, 2047]
-%1 = 300                 # ClearScalar<uint9>             ∈ [300, 300]
-%2 = add(%0, %1)         # EncryptedScalar<uint12>        ∈ [1324, 2347]
-%3 = subgraph(%2)        # EncryptedScalar<int5>          ∈ [-9, 9]
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ signed integers are only supported up to 8-bits on circuits with table lookups
-return %3
-
-Subgraphs:
-
-    %3 = subgraph(%2):
-
-        %0 = input                         # EncryptedScalar<uint2>
-        %1 = sin(%0)                       # EncryptedScalar<float64>
-        %2 = 10                            # ClearScalar<uint4>
-        %3 = multiply(%2, %1)              # EncryptedScalar<float64>
-        %4 = astype(%3, dtype=int_)        # EncryptedScalar<uint1>
-        return %4
-
             """,  # noqa: E501
         ),
     ],