Initialization on `meta` device failing for models containing `nn.utils.weight_norm`, with `NotImplementedError: Could not run 'aten::_weight_norm_interface' with arguments from the 'Meta' backend.`
Labels: triaged, actionable, module: meta tensors

### 🐛 Describe the bug

As in the title, Hubert contains a `nn.utils.weight_norm`: https://github.com/huggingface/transformers/blob/3ec8171bedff6139a23dff192b9e8af33c1fca9a/src/transformers/models/hubert/modeling_hubert.py#L283 . Trying to load it on `meta` device fails.

Minimal reproduction:
```python
import torch
import torch.nn as nn

class Model(nn.Module):
    def __init__(self):
        super().__init__()
        self.lin = nn.Linear(10, 20)
        self.lin = nn.utils.weight_norm(self.lin, name="weight", dim=1)

    def forward(self, x):
        return self.lin(x)

with torch.device("meta"):
    model = Model()
```

raising:
```
Traceback (most recent call last):
  File "/home/fxmarty/test_spda.py", line 32, in <module>
    model = Model()
  File "/home/fxmarty/test_spda.py", line 26, in __init__
    self.lin = nn.utils.weight_norm(self.lin, name="weight", dim=1)
  File "/home/fxmarty/anaconda3/envs/hf-inf/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py", line 109, in weight_norm
    WeightNorm.apply(module, name, dim)
  File "/home/fxmarty/anaconda3/envs/hf-inf/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py", line 50, in apply
    setattr(module, name, fn.compute_weight(module))
  File "/home/fxmarty/anaconda3/envs/hf-inf/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py", line 25, in compute_weight
    return _weight_norm(v, g, self.dim)
  File "/home/fxmarty/anaconda3/envs/hf-inf/lib/python3.9/site-packages/torch/utils/_device.py", line 63, in __torch_function__
    return func(*args, **kwargs)
NotImplementedError: Could not run 'aten::_weight_norm_interface' with arguments
 from the 'Meta' backend. This could be because the operator doesn't exist for t
his 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 vi
sit https://fburl.com/ptmfixes for possible resolutions. 'aten::_weight_norm_int
erface' is only available for these backends: [CPU, CUDA, BackendSelect, Python,
 FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroT
ensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradHIP, A
utogradXLA, AutogradMPS, AutogradIPU, AutogradXPU, AutogradHPU, AutogradVE, Auto
gradLazy, AutogradMeta, AutogradMTIA, AutogradPrivateUse1, AutogradPrivateUse2, 
AutogradPrivateUse3, AutogradNestedTensor, Tracer, AutocastCPU, AutocastCUDA, Fu
ncTorchBatched, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, Pyth
onTLSSnapshot, FuncTorchDynamicLayerFrontMode, PythonDispatcher].

CPU: registered at aten/src/ATen/RegisterCPU.cpp:31085 [kernel]
CUDA: registered at aten/src/ATen/RegisterCUDA.cpp:44060 [kernel]
BackendSelect: fallthrough registered at ../aten/src/ATen/core/BackendSelectFallbackKernel.cpp:3 [backend fallback]
Python: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:144 [backend fallback]
FuncTorchDynamicLayerBackMode: registered at ../aten/src/ATen/functorch/DynamicLayer.cpp:491 [backend fallback]
Functionalize: registered at ../aten/src/ATen/FunctionalizeFallbackKernel.cpp:290 [backend fallback]
Named: registered at ../aten/src/ATen/core/NamedRegistrations.cpp:7 [backend fallback]
Conjugate: registered at ../aten/src/ATen/ConjugateFallback.cpp:17 [backend fallback]
Negative: registered at ../aten/src/ATen/native/NegateFallback.cpp:19 [backend fallback]
ZeroTensor: registered at ../aten/src/ATen/ZeroTensorFallback.cpp:86 [backend fallback]
ADInplaceOrView: fallthrough registered at ../aten/src/ATen/core/VariableFallbackKernel.cpp:63 [backend fallback]
AutogradOther: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradCPU: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradCUDA: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradHIP: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradXLA: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradMPS: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradIPU: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradXPU: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradHPU: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradVE: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradLazy: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradMeta: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradMTIA: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradPrivateUse1: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradPrivateUse2: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradPrivateUse3: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
AutogradNestedTensor: registered at ../torch/csrc/autograd/generated/VariableType_0.cpp:15861 [autograd kernel]
Tracer: registered at ../torch/csrc/autograd/generated/TraceType_0.cpp:16728 [kernel]
AutocastCPU: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:487 [backend fallback]
AutocastCUDA: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:354 [backend fallback]
FuncTorchBatched: registered at ../aten/src/ATen/functorch/LegacyBatchingRegistrations.cpp:815 [backend fallback]
FuncTorchVmapMode: fallthrough registered at ../aten/src/ATen/functorch/VmapModeRegistrations.cpp:28 [backend fallback]
Batched: registered at ../aten/src/ATen/LegacyBatchingRegistrations.cpp:1073 [backend fallback]
VmapMode: fallthrough registered at ../aten/src/ATen/VmapModeRegistrations.cpp:33 [backend fallback]
FuncTorchGradWrapper: registered at ../aten/src/ATen/functorch/TensorWrapper.cpp:210 [backend fallback]
PythonTLSSnapshot: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:152 [backend fallback]
FuncTorchDynamicLayerFrontMode: registered at ../aten/src/ATen/functorch/DynamicLayer.cpp:487 [backend fallback]
PythonDispatcher: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:148 [backend fallback]
```

### Versions

PyTorch version: 2.1.0.dev20230302+cu117
Is debug build: False
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: 14.0.0-1ubuntu1
CMake version: version 3.25.0
Libc version: glibc-2.35

Python version: 3.9.12 (main, Apr  5 2022, 06:56:58)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.15.0-67-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 11.7.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3060 Laptop GPU
Nvidia driver version: 515.86.01
cuDNN version: Probably one of the following:
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn.so.8.6.0
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.6.0
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.6.0
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.6.0
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.6.0
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.6.0
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.6.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                    x86_64
CPU op-mode(s):                  32-bit, 64-bit
Address sizes:                   46 bits physical, 48 bits virtual
Byte Order:                      Little Endian
CPU(s):                          20
On-line CPU(s) list:             0-19
Vendor ID:                       GenuineIntel
Model name:                      12th Gen Intel(R) Core(TM) i7-1280P
CPU family:                      6
Model:                           154
Thread(s) per core:              2
Core(s) per socket:              14
Socket(s):                       1
Stepping:                        3
CPU max MHz:                     4800,0000
CPU min MHz:                     400,0000
BogoMIPS:                        3993.60
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l2 invpcid_single cdp_l2 ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdt_a rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req umip pku ospke waitpkg gfni vaes vpclmulqdq tme rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr flush_l1d arch_capabilities
Virtualization:                  VT-x
L1d cache:                       544 KiB (14 instances)
L1i cache:                       704 KiB (14 instances)
L2 cache:                        11,5 MiB (8 instances)
L3 cache:                        24 MiB (1 instance)
NUMA node(s):                    1
NUMA node0 CPU(s):               0-19
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Mmio stale data:   Not affected
Vulnerability Retbleed:          Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:        Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.23.5
[pip3] pytorch-triton==2.0.0+b8b470bc59
[pip3] torch==2.1.0.dev20230302+cu117
[pip3] torch-model-archiver==0.6.1
[pip3] torch-workflow-archiver==0.2.5
[pip3] torchaudio==2.0.0.dev20230302+cu117
[pip3] torchinfo==1.7.0
[pip3] torchserve==0.6.1
[pip3] torchtriton==2.0.0+0d7e753227
[pip3] torchvision==0.15.0.dev20230302+cu117
[conda] cudatoolkit               11.3.1               h2bc3f7f_2    anaconda
[conda] numpy                     1.23.5                   pypi_0    pypi
[conda] pytorch-triton            2.0.0+b8b470bc59          pypi_0    pypi
[conda] torch                     2.1.0.dev20230302+cu117          pypi_0    pypi
[conda] torch-model-archiver      0.6.1                    pypi_0    pypi
[conda] torch-workflow-archiver   0.2.5                    pypi_0    pypi
[conda] torchaudio                2.0.0.dev20230302+cu117          pypi_0    pypi
[conda] torchinfo                 1.7.0                    pypi_0    pypi
[conda] torchserve                0.6.1                    pypi_0    pypi
[conda] torchtriton               2.0.0+0d7e753227          pypi_0    pypi
[conda] torchvision               0.15.0.dev20230302+cu117          pypi_0    pypi


cc @ezyang @eellison @bdhirsh @soumith