Repository: pytorch
Issue: ValueError: weight_norm of 'weight' not found in ParametrizedConvTranspose1d
Labels: triaged,module: nn.utils.parametrize

### 🐛 Describe the bug

Hi,
  I'm trying to wrap and unwrap weight normalization and I get an error.  Strangely it is complaining about `weight` not be present where we can see it when printing the model.

I was seeing `warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")` in my logs thus I decided to change the deprecated function for the suggested one and then I started to get the error.  If we change `from torch.nn.utils.parametrizations import weight_norm` back to `from torch.nn.utils import remove_weight_norm, weight_norm`, we get a succes.



# Code

```python
#!/usr/bin/env  python3
# coding: utf-8

from torch.nn import ConvTranspose1d
from torch.nn.utils import remove_weight_norm
from torch.nn.utils.parametrizations import weight_norm

c = ConvTranspose1d(512, 256, kernel_size=(16,), stride=(8,), padding=(4,))
print(c)
m = weight_norm(c)
print(m)
remove_weight_norm(m)
```

# Error

```
ConvTranspose1d(512, 256, kernel_size=(16,), stride=(8,), padding=(4,))
ParametrizedConvTranspose1d(
  512, 256, kernel_size=(16,), stride=(8,), padding=(4,)
  (parametrizations): ModuleDict(
    (weight): ParametrizationList(
      (0): _WeightNorm()
    )
  )
)

Traceback (most recent call last):
  File "$HOME/norm_weight_error.py", line 10, in <module>
    remove_weight_norm(m)
  File "$HOME/.conda/envs/test/lib/python3.11/site-packages/torch/nn/utils/weight_norm.py", line 153, in remove_weight_norm
    raise ValueError(f"weight_norm of '{name}' not found in {module}")
ValueError: weight_norm of 'weight' not found in ParametrizedConvTranspose1d(
  512, 256, kernel_size=(16,), stride=(8,), padding=(4,)
  (parametrizations): ModuleDict(
    (weight): ParametrizationList(
      (0): _WeightNorm()
    )
  )
)
```

### Versions

Collecting environment information...
PyTorch version: 2.1.0+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.11.7 (main, Dec 15 2023, 18:12:31) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-102-generic-x86_64-with-glibc2.35
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: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      48 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             128
On-line CPU(s) list:                0-127
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 7532 32-Core Processor
CPU family:                         23
Model:                              49
Thread(s) per core:                 2
Core(s) per socket:                 32
Socket(s):                          2
Stepping:                           0
Frequency boost:                    enabled
CPU max MHz:                        2400.0000
CPU min MHz:                        1500.0000
BogoMIPS:                           4791.10
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good
 nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misaligns
se 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdsee
d adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmc
b_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca
Virtualization:                     AMD-V
L1d cache:                          2 MiB (64 instances)
L1i cache:                          2 MiB (64 instances)
L2 cache:                           32 MiB (64 instances)
L3 cache:                           512 MiB (32 instances)
NUMA node(s):                       2
NUMA node0 CPU(s):                  0-31,64-95
NUMA node1 CPU(s):                  32-63,96-127
Vulnerability Gather data sampling: Not affected
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:             Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow: Mitigation; safe RET
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; Retpolines, IBPB conditional, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] flake8==7.0.0
[pip3] mypy==1.8.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] pytorch-lightning==2.2.0.post0
[pip3] torch==2.1.0+cu118
[pip3] torchaudio==2.1.0+cu118
[pip3] torchinfo==1.8.0
[pip3] torchmetrics==1.3.1
[pip3] triton==2.1.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] pytorch-lightning         2.2.0.post0              pypi_0    pypi
[conda] torch                     2.1.0+cu118              pypi_0    pypi
[conda] torchaudio                2.1.0+cu118              pypi_0    pypi
[conda] torchinfo                 1.8.0                    pypi_0    pypi
[conda] torchmetrics              1.3.1                    pypi_0    pypi
[conda] triton                    2.1.0                    pypi_0    pypi