提出 #506563: pytorch 2.6.0+cu124 Inconsistency Between Implementation and Documented Design

### ???? Describe the bug

There seems to be an issue in PyTorch's quantized Sigmoid module (nnq_Sigmoid) where the quantization parameters (scale and zero_point) are not properly restored when loading the state dictionary (state_dict) into a newly initialized module with different initial parameters.

Code:
```
import torch
from torch.ao.nn.quantized import Sigmoid as nnq_Sigmoid

def test_sigmoid_serialization():
# Original parameters
scale_original = 0.1
zero_point_original = 5

# Create original module and save state
quant_mod_original = nnq_Sigmoid(scale_original, zero_point_original)
state_dict = quant_mod_original.state_dict()

# New parameters (different from original)
scale_new = 0.5
zero_point_new = 10

# Create new module and load original state
quant_mod_new = nnq_Sigmoid(scale_new, zero_point_new)
quant_mod_new.load_state_dict(state_dict)

# Check if parameters were restored
print("quant_mod_new.output_scale:", quant_mod_new.output_scale)
print("scale_original: ", scale_original)

print("quant_mod_new.output_zero_point:", quant_mod_new.output_zero_point)
print("zero_point_original:", zero_point_original)

test_sigmoid_serialization()
```

Output:
The parameters scale and zero_point are not restored correctly after loading the state dictionary. The output shows that the parameters are not matching the original values, which implies that the state dictionary is not correctly restoring the quantization parameters.
```
quant_mod_new.output_scale: 0.5
scale_original: 0.1
quant_mod_new.output_zero_point: 10
zero_point_original: 5
```

### Versions

PyTorch version: 2.6.0+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

• ソース: ⚠️ https://github.com/pytorch/pytorch/issues/147818
• ユーザー: Default436352 (UID 81891)
• 送信: 2025年02月25日 08:03 (2 年 ago)
• モデレーション: 2025年03月10日 07:14 (13 days later)
• ステータス: 承諾済み
• VulDBエントリ: 299060 [PyTorch 2.6.0+cu124 Quantized Sigmoid nnq_Sigmoid scale/zero_point]
• ポイント: 20