new backend privateuseone with "to" op
Labels: triaged, module: backend

### 🐛 Describe the bug

when I use a new backend with the key of privateuseone, and  we have implement for the op of "to" with backend like this.  I think it is an error with the dispatchkey of "AutogradPrivateUse1", So  I do some tests for the bakcend. 

### test_code 

I add to_dtype func based on test cpp_extensions/open_registration_extension.cpp, link
https://github.com/heidongxianhua/pytorch/commit/fdb57dac418ec849dfd7900b1b69e815840b06b5

 And when run the test with python3 test_cpp_extensions_open_device_registration.py, It dose not work and got error message is here. I check the to_dtype func have been registered for PrivateUse1  backend 
```
Fail to import hypothesis in common_utils, tests are not derandomized
Using /root/.cache/torch_extensions/py38_cpu as PyTorch extensions root...
Creating extension directory /root/.cache/torch_extensions/py38_cpu/custom_device_extension...
Emitting ninja build file /root/.cache/torch_extensions/py38_cpu/custom_device_extension/build.ninja...
Building extension module custom_device_extension...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] c++ -MMD -MF open_registration_extension.o.d -DTORCH_EXTENSION_NAME=custom_device_extension -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/shibo/device_type/pytorch_shibo/test/cpp_extensions -isystem /root/anaconda3/envs/shibo2/lib/python3.8/site-packages/torch/include -isystem /root/anaconda3/envs/shibo2/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /root/anaconda3/envs/shibo2/lib/python3.8/site-packages/torch/include/TH -isystem /root/anaconda3/envs/shibo2/lib/python3.8/site-packages/torch/include/THC -isystem /root/anaconda3/envs/shibo2/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=1 -fPIC -std=c++17 -g -c /home/shibo/device_type/pytorch_shibo/test/cpp_extensions/open_registration_extension.cpp -o open_registration_extension.o
[2/2] c++ open_registration_extension.o -shared -L/root/anaconda3/envs/shibo2/lib/python3.8/site-packages/torch/lib -lc10 -ltorch_cpu -ltorch -ltorch_python -o custom_device_extension.so
Loading extension module custom_device_extension...
E
======================================================================
ERROR: test_open_device_registration (__main__.TestCppExtensionOpenRgistration)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "test_cpp_extensions_open_device_registration.py", line 78, in test_open_device_registration
    y_int32 = y.to(torch.int32)
NotImplementedError: Could not run 'aten::to.dtype' with arguments from the 'AutogradPrivateUse1' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'aten::to.dtype' is only available for these backends: [CPU, CUDA, HIP, XLA, MPS, IPU, XPU, HPU, VE, Lazy, Meta, MTIA, PrivateUse1, PrivateUse2, PrivateUse3, FPGA, ORT, Vulkan, Metal, QuantizedCPU, QuantizedCUDA, QuantizedHIP, QuantizedXLA, QuantizedMPS, QuantizedIPU, QuantizedXPU, QuantizedHPU, QuantizedVE, QuantizedLazy, QuantizedMeta, QuantizedMTIA, QuantizedPrivateUse1, QuantizedPrivateUse2, QuantizedPrivateUse3, CustomRNGKeyId, MkldnnCPU, SparseCPU, SparseCUDA, SparseHIP, SparseXLA, SparseMPS, SparseIPU, SparseXPU, SparseHPU, SparseVE, SparseLazy, SparseMeta, SparseMTIA, SparsePrivateUse1, SparsePrivateUse2, SparsePrivateUse3, SparseCsrCPU, SparseCsrCUDA, NestedTensorCPU, NestedTensorCUDA, NestedTensorHIP, NestedTensorXLA, NestedTensorMPS, NestedTensorIPU, NestedTensorXPU, NestedTensorHPU, NestedTensorVE, NestedTensorLazy, NestedTensorMeta, NestedTensorMTIA, NestedTensorPrivateUse1, NestedTensorPrivateUse2, NestedTensorPrivateUse3, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradHIP, AutogradXLA, AutogradMPS, AutogradIPU, AutogradXPU, AutogradHPU, AutogradVE, AutogradLazy, AutogradMeta, AutogradMTIA, AutogradPrivateUse2, AutogradPrivateUse3, AutogradNestedTensor, Tracer, AutocastCPU, AutocastCUDA, FuncTorchBatched, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PythonDispatcher]

Undefined: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
CPU: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
CUDA: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
HIP: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
XLA: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
MPS: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
IPU: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
XPU: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
HPU: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
VE: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
Lazy: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
Meta: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
MTIA: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
PrivateUse1: registered at /home/shibo/device_type/pytorch_shibo/test/cpp_extensions/open_registration_extension.cpp:90 [kernel]
PrivateUse2: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
PrivateUse3: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
FPGA: registered at /home/shibo/device_type/pytorch_test/build/aten/src/ATen/RegisterCompositeImplicitAutograd.cpp:7140 [math kernel]
............

```


### Versions


```
Collecting environment information...
 PyTorch version: 2.0.0a0+git900db22
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.4 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: 8.0.1  (based on LLVM 8.0.1)
CMake version: version 3.24.1
Libc version: glibc-2.27

Python version: 3.8.13 (default, Mar 28 2022, 11:38:47)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-4.15.0-76-generic-x86_64-with-glibc2.17
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: False

Versions of relevant libraries:
[pip3] numpy==1.24.2
[pip3] torch==2.0.0a0+git2f0b0c5
[pip3] torch-npu==2.0.0
[conda] numpy                     1.24.2                   pypi_0    pypi
[conda] torch                     2.0.0a0+git900db22          pypi_0    pypi
[conda] torch-npu                 2.0.0                    pypi_0    pypi


```