Fix max_pool2d decomposition for empty list and integer limits (#129106)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129106
Approved by: https://github.com/peterbell10, https://github.com/lezcano, https://github.com/malfet
ghstack dependencies: #129096, #129097

test/inductor/test_torchinductor_opinfo.py

diff --git a/test/inductor/test_torchinductor_opinfo.py b/test/inductor/test_torchinductor_opinfo.py
index 4a42c52..93dd2a0 100644
--- a/test/inductor/test_torchinductor_opinfo.py
+++ b/test/inductor/test_torchinductor_opinfo.py
@@ -439,7 +439,6 @@
     "nn.functional.gaussian_nll_loss": {f16},
     "nn.functional.grid_sample": {f32, f64},
     "nn.functional.interpolate.area": {f16},
-    "nn.functional.max_pool2d": {f16, f32, f64, i32, i64},
     "nn.functional.nll_loss": {f16, f32, f64},
     "normal": {f16, f32, f64},
     "put": {f16, f32, f64},

test/nn/test_pooling.py

diff --git a/test/nn/test_pooling.py b/test/nn/test_pooling.py
index eae5370..2175067 100644
--- a/test/nn/test_pooling.py
+++ b/test/nn/test_pooling.py
@@ -1120,6 +1120,34 @@
         helper(10, 512, 31, 31, 3, stride=2)
         helper(1, 129, 8, 8, 3, stride=2)
 
+    @onlyCPU
+    @dtypes(torch.int32, torch.int64)
+    def test_max_pool2d_corner_cases(self, device, dtype):
+        def check(x, args, expected, memory_format):
+            model = torch.nn.MaxPool2d(*args)
+            if isinstance(x, list):
+                x = torch.tensor(x, device=device, dtype=dtype).to(
+                    memory_format=memory_format
+                )
+                expected = torch.tensor(expected, device=device, dtype=dtype).to(
+                    memory_format=memory_format
+                )
+            self.assertEqual(model(x), expected)
+
+        # Pooling args: (kernel_size, stride, padding, dilation, return_indices, ceil_mode)
+        check(
+            [[[[-1, -2], [-3, -4]]]],
+            (2, 2, 1, 2, False, True),
+            [[[[-4, -4], [-4, -4]]]],
+            torch.contiguous_format,
+        )
+        check(
+            [[[[-1, -2], [-3, -4]]]],
+            (2, 2, 1, 2, False, True),
+            [[[[-4, -4], [-4, -4]]]],
+            torch.channels_last,
+        )
+
     @onlyNativeDeviceTypes
     @dtypes(torch.half, torch.bfloat16, torch.float, torch.double)
     @dtypesIfCUDA(torch.half, torch.float, torch.double)

test/test_mps.py

diff --git a/test/test_mps.py b/test/test_mps.py
index 77f3198..54b47d1 100644
--- a/test/test_mps.py
+++ b/test/test_mps.py
@@ -731,9 +731,6 @@
         'nn.functional.interpolatearea': None,
         'nn.functional.interpolatebicubic': None,
         'nn.functional.interpolatetrilinear': None,
-        # TODO: max_pool2d for integral types fails the numerical test
-        'nn.functional.max_pool2d': (integral_types() if product_version < 14.0 else
-                                     [torch.int64, torch.int32, torch.int16, torch.int8]),
         'nn.functional.max_unpool1dgrad': None,
         'nn.functional.max_unpool2dgrad': None,
         'nn.functional.max_unpool3dgrad': None,
@@ -911,6 +908,7 @@
             # Error in TestConsistencyCPU.test_output_match_isin_cpu fails for integers,
             # not reproducible in later OS. Added assert to op if used in < 14.0
             'isin': [torch.int64, torch.int32, torch.int16, torch.uint8, torch.int8],
+            'nn.functional.max_pool2d': [torch.uint8],
         })
 
     UNDEFINED_XFAILLIST = {