RuntimeError: Currently topk on mps works only for k<=16 in Apple silicon GPU (device = MPS)

## Instructions To Reproduce the 🐛 Bug:
I am trying to run detectron2 demo code from google colab in my system which has apple silicon GPU but I am encountering an error.

### Reproduction steps:
#### 1. Download sample image from coco dataset using the following command:
```
!wget http://images.cocodataset.org/val2017/000000439715.jpg -q -O input.jpg
```
#### 2. Run the following code:
It is the same code from the front page. Link: https://github.com/facebookresearch/detectron2#:~:text=%2C%20and%20the-,Colab%20Notebook,-to%20learn%20about

```
# Some basic setup:
# Setup detectron2 logger
import detectron2
from detectron2.utils.logger import setup_logger

setup_logger()

# import some common libraries
import numpy as np
import os, json, cv2, random
import matplotlib.pyplot as plt

# import some common detectron2 utilities
from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
from detectron2.config import get_cfg
from detectron2.utils.visualizer import Visualizer
from detectron2.data import MetadataCatalog, DatasetCatalog

cfg = get_cfg()

# This line is added to set device to "mps"
cfg.MODEL.DEVICE = "mps"

# add project-specific config (e.g., TensorMask) here if you're not running a model in detectron2's core library
cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml"))
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 # set threshold for this model
# Find a model from detectron2's model zoo. You can use the https://dl.fbaipublicfiles... url as well
cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml")
predictor = DefaultPredictor(cfg)

# !wget http://images.cocodataset.org/val2017/000000439715.jpg -q -O input.jpg
im = cv2.imread("input.jpg")
plt.imshow(im)

outputs = predictor(I'm)
print(outputs)
```
## 3. Actual output
```
WARNING:root:Pytorch pre-release version 1.13.0.dev20220618 - assuming intent to test it
/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/TensorShape.cpp:2890.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
Traceback (most recent call last):
File "/Users/bikram/PycharmProjects/detectron-example/main.py", line 33, in
outputs = predictor(im)
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/engine/defaults.py", line 317, in __call__
predictions = self.model([inputs])[0]
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1131, in _call_impl
return forward_call(*input, **kwargs)
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 150, in forward
return self.inference(batched_inputs)
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 208, in inference
proposals, _ = self.proposal_generator(images, features, None)
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1131, in _call_impl
return forward_call(*input, **kwargs)
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/modeling/proposal_generator/rpn.py", line 478, in forward
anchors, pred_objectness_logits, pred_anchor_deltas, images.image_sizes
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/modeling/proposal_generator/rpn.py", line 511, in predict_proposals
self.training,
File "/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/modeling/proposal_generator/proposal_utils.py", line 79, in find_top_rpn_proposals
topk_scores_i, topk_idx = logits_i.topk(num_proposals_i, dim=1)
RuntimeError: Currently topk on mps works only for k<=16
```
## Expected output:
When the device is set to "CPU" on the same system, I get the following outputs without any error:
```
{'instances': Instances(num_instances=15, image_height=480, image_width=640, fields=[pred_boxes: Boxes(tensor([[126.6035, 244.8977, 459.8291, 480.0000],
[251.1083, 157.8127, 338.9731, 413.6379],
[114.8496, 268.6864, 148.2352, 398.8111],
[ 0.8217, 281.0327, 78.6072, 478.4210],
[ 49.3954, 274.1229, 80.1545, 342.9808],
[561.2248, 271.5816, 596.2755, 385.2552],
[385.9072, 270.3125, 413.7130, 304.0397],
[515.9295, 278.3744, 562.2792, 389.3803],
[335.2409, 251.9167, 414.7491, 275.9375],
[350.9300, 269.2060, 386.0984, 297.9081],
[331.6292, 230.9996, 393.2759, 257.2009],
[510.7349, 263.2656, 570.9865, 295.9194],
[409.0841, 271.8646, 460.5582, 356.8722],
[506.8767, 283.3257, 529.9403, 324.0392],
[594.5663, 283.4820, 609.0577, 311.4124]])), scores: tensor([0.9997, 0.9957, 0.9915, 0.9882, 0.9861, 0.9840, 0.9769, 0.9716, 0.9062,
0.9037, 0.8870, 0.8575, 0.6592, 0.5899, 0.5767]), pred_classes: tensor([17, 0, 0, 0, 0, 0, 0, 0, 25, 0, 25, 25, 0, 0, 24]), pred_masks: tensor([[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
...,
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],

[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
...,
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],

[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
...,
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],

...,

[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
...,
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],

[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
...,
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],

[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
...,
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]]])])}
```
## Environment:
Provide your environment information using the following command:
```
--------------------- --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
sys.platform darwin
Python 3.7.13 (default, Mar 28 2022, 07:24:34) [Clang 12.0.0 ]
numpy 1.21.6
detectron2 0.6 @/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2
detectron2._C not built correctly: dlopen(/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/_C.cpython-37m-darwin.so, 0x0002): Symbol not found: __ZN2at5emptyEN3c108ArrayRefIxEENS0_13TensorOptionsENS0_8optionalINS0_12MemoryFormatEEE
Referenced from: /Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/detectron2/_C.cpython-37m-darwin.so
Expected in: /Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/torch/lib/libtorch_cpu.dylib
Compiler ($CXX) Apple clang version 13.1.6 (clang-1316.0.21.2.5)
DETECTRON2_ENV_MODULE
PyTorch 1.13.0.dev20220618 @/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/torch
PyTorch debug build False
GPU available No: torch.cuda.is_available() == False
Pillow 9.1.1
torchvision 0.14.0.dev20220618 @/Users/bikram/miniforge3/envs/mcs2/lib/python3.7/site-packages/torchvision
fvcore 0.1.5.post20220512
iopath 0.1.9
cv2 4.6.0
--------------------- --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
PyTorch built with:
- GCC 4.2
- C++ Version: 201402
- clang 13.1.6
- Intel(R) Math Kernel Library Version 2020.0.1 Product Build 20200208 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815)
- OpenMP 201811
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: NO AVX
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CXX_COMPILER=/Applications/Xcode_13.3.1.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -Wno-deprecated-declarations -DUSE_PTHREADPOOL -Xpreprocessor -fopenmp -I/usr/local/include -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_PYTORCH_METAL_EXPORT -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -DUSE_COREML_DELEGATE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-range-loop-analysis -Wno-pass-failed -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-typedef-redefinition -Wno-unknown-warning-option -Wno-unused-private-field -Wno-inconsistent-missing-override -Wno-aligned-allocation-unavailable -Wno-c++14-extensions -Wno-constexpr-not-const -Wno-missing-braces -Qunused-arguments -fcolor-diagnostics -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -DUSE_MPS -fno-objc-arc -Wno-unused-private-field -Wno-missing-braces -Wno-c++14-extensions -Wno-constexpr-not-const, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.0, USE_CUDA=OFF, USE_CUDNN=OFF, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,
```

Start with modeling/proposal_generator/proposal_utils.py at find_top_rpn_proposals, where the traceback reaches logits_i.topk, and reproduce the demo using the reported PyTorch and MPS environment. Compare MPS behavior with the working CPU path and verify that the Detectron2 demo completes without the topk runtime error.

Written by the indexing model from the issue text.