Update on "[ET-VK][Ops] aten.avg_pool2d"

## The Operator
`nn.Module` invocations of [`torch.nn.AvgPool2d`](https://pytorch.org/docs/stable/generated/torch.nn.AvgPool2d.html) get compiled to `aten.avg_pool2d.default` in the Edge Dialect, which carries the following signature.
```
- func: avg_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor
```

## Implementation
This is a full implementation. We start with [LiteInterpreter's `avg_pool2d.glsl` logic](https://github.com/pytorch/pytorch/blob/9257a0698b57acc5607ee6fe31a16fdd93af1731/aten/src/ATen/native/vulkan/glsl/avg_pool2d.glsl), which is incomplete, and cover `ceil_mode=True`,  `count_include_pad=True`, and `divisor_override` cases for full support. As a result, the divisor's computation is now a bit complex. If needed, we can simplify it into separate shaders in the future.

Differential Revision: [D57918523](https://our.internmc.facebook.com/intern/diff/D57918523/)

[ghstack-poisoned]

Author: jorgep31415

backends/vulkan/test/op_tests/cases.py

@@ -144,28 +144,28 @@ def get_avg_pool2d_inputs():
                         count_include_pad=count_include_pad,
                         divisor_override=divisor_override,
                     ),
-                    Test(
-                        self=(S, M1, M2),
-                        kernel_size=[5, 4],
-                        stride=[3, 1],
-                        padding=[2, 1],
-                        ceil_mode=ceil_mode,
-                        count_include_pad=count_include_pad,
-                        divisor_override=divisor_override,
-                    ),
-                    Test(
-                        self=(S, M1, M2),
-                        kernel_size=[4, 5],
-                        stride=[1, 3],
-                        padding=[2, 1],
-                        ceil_mode=ceil_mode,
-                        count_include_pad=count_include_pad,
-                        divisor_override=divisor_override,
-                    ),
                 ]
-
+        test_cases += [
+            Test(
+                self=(S, M1, M2),
+                kernel_size=[5, 4],
+                stride=[3, 1],
+                padding=[2, 1],
+                ceil_mode=ceil_mode,
+                count_include_pad=True,
+                divisor_override=None,
+            ),
+            Test(
+                self=(S, M1, M2),
+                kernel_size=[4, 5],
+                stride=[1, 3],
+                padding=[2, 1],
+                ceil_mode=ceil_mode,
+                count_include_pad=True,
+                divisor_override=None,
+            ),
+        ]
     test_suite = VkTestSuite([tuple(tc) for tc in test_cases])
-    test_suite.dtypes = ["at::kFloat"]
     return test_suite