Repository: pytorch
Issue: simple v *=  v_scale error
Labels: module: autograd,triaged,actionable

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->

## To Reproduce

Steps to reproduce the behavior:
v *= v_scale

RuntimeError: diff_view_meta->output_nr_ == 0 INTERNAL ASSERT FAILED at "../torch/csrc/autograd/variable.cpp":363, please report a bug to PyTorch. 

I printed the v value as

tensor([[[[ 1.2014e-02,  1.2068e-02,  9.7856e-03,  8.8714e-03,  8.5734e-03,
            2.9168e-03,  2.1199e-05, -2.8829e-03, -8.2607e-03, -1.5328e-02,
           -2.5013e-02, -3.1222e-02],
          [ 1.0266e-02,  6.2610e-03,  5.2078e-03,  5.4408e-03,  4.0872e-03,
           -5.5038e-04, -4.3396e-03, -7.8755e-03, -1.2391e-02, -1.8298e-02,
           -2.3656e-02, -2.3437e-02],
          [ 5.6735e-03,  4.5379e-03,  3.9397e-03,  4.7426e-03,  1.8061e-03,
           -2.3692e-03, -7.8620e-03, -1.2199e-02, -1.4298e-02, -1.7047e-02,
           -2.0498e-02, -2.0740e-02],
          [ 8.3388e-03,  5.1143e-03,  2.9209e-03,  5.5275e-03,  2.9254e-03,
           -2.9371e-04, -4.7937e-03, -1.0673e-02, -1.2947e-02, -1.5372e-02,
           -1.9295e-02, -2.1778e-02],
          [ 8.7581e-03,  7.9502e-03,  7.1754e-03,  7.7227e-03,  6.9899e-03,
            5.8939e-03,  5.0108e-03, -7.9185e-03, -9.1207e-03, -1.3086e-02,
           -1.6816e-02, -2.1605e-02],
          [ 7.9434e-03,  6.1096e-03,  3.8051e-03,  3.1724e-03,  2.2082e-03,
            2.1375e-03, -2.9212e-04, -3.9539e-03, -7.1065e-03, -1.2883e-02,
           -1.7969e-02, -2.4725e-02]]],    [[[ 6.5310e-02,  5.6975e-02,  4.5132e-02,  5.0792e-02,  5.6704e-02,
            6.2313e-02,  6.5036e-02,  6.4221e-02,  5.9827e-02,  6.2116e-02,
            6.5767e-02,  7.4780e-02],
          [ 5.6775e-02,  5.0288e-02,  5.4376e-02,  6.2040e-02,  6.0906e-02,
            5.9159e-02,  5.9787e-02,  6.1453e-02,  5.8250e-02,  5.6893e-02,
            6.1770e-02,  6.7854e-02],
          [ 4.7995e-02,  4.8208e-02,  5.2908e-02,  5.5330e-02,  6.1871e-02,
            5.6681e-02,  5.6556e-02,  6.0526e-02,  5.0920e-02,  5.3691e-02,
            5.8827e-02,  6.3531e-02],
          [ 3.0758e-02,  4.0276e-02,  4.7759e-02,  4.0098e-02,  4.0556e-02,
            3.1987e-02,  3.8289e-02,  4.4429e-02,  4.1669e-02,  4.7020e-02,
            5.2110e-02,  5.7387e-02],
          [ 1.5687e-02,  2.2496e-02,  2.2303e-02,  3.8733e-03, -7.9459e-03,
           -1.0541e-02, -6.2762e-03,  1.3099e-02,  2.7646e-02,  3.7377e-02,
            4.5027e-02,  4.2339e-02],
          [-1.0777e-02, -1.2646e-02, -1.3509e-02, -1.3324e-02, -1.8688e-02,
           -3.3734e-02, -2.8426e-02, -1.3815e-02,  6.6503e-03,  1.6921e-02, 3.4458e-02,  3.6185e-02]]]], device='cuda:0',grad_fn=SplitBackward )

v_scale = 3.2000000000000006

Is very strange that there is error during the mulitplcation of a scaler with a tensor.
I guess the errors occurs at the autograd backward part

## Expected behavior

<!-- A clear and concise description of what you expected to happen. -->

## Environment

Please copy and paste the output from our
[environment collection script](https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py)
(or fill out the checklist below manually).

You can get the script and run it with:
```
wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py
# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
```
Collecting environment information...
PyTorch version: 1.8.0a0+37dbc61
Is debug build: True
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.1 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: 10.0.0-4ubuntu1 
CMake version: version 3.18.2

Python version: 3.8 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: GeForce RTX 3090
Nvidia driver version: 455.32.00
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.0.4
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.19.1
[pip3] torch==1.8.0a0
[pip3] torchvision==0.8.0a0+cffac64
[conda] blas                      1.0                         mkl  
[conda] magma-cuda110             2.5.2                         1    pytorch
[conda] mkl                       2020.2                      256  
[conda] mkl-include               2020.2                      256  
[conda] mkl-service               2.3.0            py38he904b0f_0  
[conda] mkl_fft                   1.2.0            py38h23d657b_0  
[conda] mkl_random                1.1.1            py38h0573a6f_0  
[conda] numpy                     1.19.1           py38hbc911f0_0  
[conda] numpy-base                1.19.1           py38hfa32c7d_0  
[conda] torch                     1.8.0a0                  pypi_0    pypi
[conda] torchvision               0.8.0a0+cffac64          pypi_0    pypi

## Additional context

<!-- Add any other context about the problem here. -->


cc @ezyang @albanD @zou3519 @gqchen @pearu @nikitaved