[API Compatibility] enhance torch.aminmax tests -part

paconvert/api_mapping.json

@@ -3335,15 +3335,7 @@
     "Matcher": "ChangePrefixMatcher"
   },
   "torch.aminmax": {
-    "Matcher": "AMinMaxMatcher",
-    "min_input_args": 1,
-    "args_list": [
-      "input",
-      "*",
-      "dim",
-      "keepdim",
-      "out"
-    ]
+    "Matcher": "ChangePrefixMatcher"
   },
   "torch.amp.autocast": {
     "Matcher": "ChangePrefixMatcher"

tests/test_aminmax.py

@@ -87,3 +87,112 @@ def test_case_6():
         """
     )
     obj.run(pytorch_code, ["out"])
+
+
+def test_case_7():
+    """1D tensor input"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([5.0, 1.0, 3.0, 9.0, 2.0])
+        result = torch.aminmax(t)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_8():
+    """3D tensor with dim=0"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]])
+        result = torch.aminmax(t, dim=0)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_9():
+    """3D tensor with dim=1 and keepdim=True"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]])
+        result = torch.aminmax(t, dim=1, keepdim=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_10():
+    """float64 dtype"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[1.5, 2.3, 3.7], [4.1, 5.9, 6.2]], dtype=torch.float64)
+        result = torch.aminmax(t, dim=1)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_11():
+    """explicit keepdim=False"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=torch.float)
+        result = torch.aminmax(t, dim=0, keepdim=False)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_12():
+    """input as keyword argument only"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.aminmax(input=torch.tensor([3.0, 1.0, 4.0, 1.0, 5.0]))
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_13():
+    """kwargs unpacking"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
+        kwargs = {"dim": 0, "keepdim": True}
+        result = torch.aminmax(t, **kwargs)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_14():
+    """expression as dim argument"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
+        result = torch.aminmax(t, dim=2 - 1)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_15():
+    """dim with out parameter and keepdim"""
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        t = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
+        out = tuple([torch.tensor([0.0, 0.0]), torch.tensor([0.0, 0.0])])
+        result = torch.aminmax(t, dim=1, keepdim=False, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["out", "result"])