Repository: pytorch
Issue: requires grad get lost during transform.
Labels: module: autograd,triaged,module: deprecation,module: tensor creation

## 🐛 Bug

If you convert a list of parameters with requires_grad=True into
a tensor, you lose the gradients.

## To Reproduce
Steps to reproduce the behavior:

```
import torch

t = torch.FloatTensor([1.0])
p = torch.nn.Parameter(t)

p.requires_grad = True

print(torch.Tensor(p).requires_grad)    # True
print(torch.Tensor([p,]).requires_grad) # False
```
## Expected behavior

The output should be equivalent with:
```
torch.stack([...], dim=0)
```
Or the code should raise an exception.

Reasoning: whatever happens, a transformation 
like this should not silently remove the requires_grad.
If legal, propagate it, if not, ban the use of it. 

## Environment

PyTorch version: 1.9.0
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 21.04 (x86_64)
GCC version: (Ubuntu 10.3.0-1ubuntu1) 10.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.33

Python version: 3.8.10 (default, Jun  4 2021, 15:09:15)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.12.0-14.2-liquorix-amd64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.3.109
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 2060
Nvidia driver version: 465.31
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
```
[pip3] botorch==0.4.0
[pip3] efficientnet-pytorch==0.6.3
[pip3] gpytorch==1.5.0
[pip3] numpy==1.19.0
[pip3] pytorch-lightning==1.3.8
[pip3] segmentation-models-pytorch==0.1.3
[pip3] torch==1.9.0
[pip3] torchist==0.1.5
[pip3] torchmetrics==0.3.2
[pip3] torchvision==0.10.0
[conda] blas                      1.0                         mkl  
[conda] botorch                   0.4.0                    pypi_0    pypi
[conda] cudatoolkit               11.1.74              h6bb024c_0    nvidia
[conda] efficientnet-pytorch      0.6.3                    pypi_0    pypi
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] gpytorch                  1.5.0                    pypi_0    pypi
[conda] mkl                       2021.2.0           h06a4308_296  
[conda] mkl-service               2.3.0            py38h27cfd23_1  
[conda] mkl_fft                   1.3.0            py38h42c9631_2  
[conda] mkl_random                1.2.1            py38ha9443f7_2  
[conda] numpy                     1.19.0                   pypi_0    pypi
[conda] pytorch                   1.9.0           py3.8_cuda11.1_cudnn8.0.5_0    pytorch
[conda] pytorch-lightning         1.3.8                    pypi_0    pypi
[conda] segmentation-models-pytorch 0.1.3                    pypi_0    pypi
[conda] torchist                  0.1.5                    pypi_0    pypi
[conda] torchmetrics              0.3.2                    pypi_0    pypi
[conda] torchvision               0.10.0               py38_cu111    pytorch
```

## Additional context

I don't think this is anyhow related to install or libraries, this should be core autograd issue / property.



cc @ezyang @albanD @zou3519 @gqchen @pearu @nikitaved @soulitzer @Lezcano @Varal7 @gchanan @mruberry @jbschlosser