Repository: pytorch
Issue: torch.utils.tensorboard.SummaryWriter.add_embedding fails for some label_img sizes
Labels: triaged,module: tensorboard

## 🐛 Bug

`torch.utils.tensorboard.SummaryWriter.add_embedding` fails for some label_img sizes.
Suspect that square and non-square width>height works, but non-square width<height fails.

## To Reproduce

```
import torch
from torch.utils.tensorboard import SummaryWriter

writer = SummaryWriter('./')
writer.add_embedding(
    torch.randn(100, 256),
    label_img=torch.randn(100, 3, 32, 32)
)

writer = SummaryWriter('./')
writer.add_embedding(
    torch.randn(100, 256),
    label_img=torch.randn(100, 3, 10, 10)
)

writer = SummaryWriter('./')
writer.add_embedding(
    torch.randn(100, 256),
    label_img=torch.randn(100, 3, 10, 32)
)

writer = SummaryWriter('./')
writer.add_embedding(
    torch.randn(100, 256),
    label_img=torch.randn(100, 3, 32, 10)
)
```

```
Traceback (most recent call last):
  File "scratch.py", line 25, in <module>
    label_img=torch.randn(100, 3, 32, 10)
  File "/home/user/.conda/envs/detectron2/lib/python3.7/site-packages/torch/utils/tensorboard/writer.py", line 805, in add_embedding
    make_sprite(label_img, save_path)
  File "/home/user/.conda/envs/detectron2/lib/python3.7/site-packages/torch/utils/tensorboard/_embedding.py", line 36, in make_sprite
    arranged_augment_square_HWC[:arranged_img_HWC.shape[0], :, :] = arranged_img_HWC
ValueError: could not broadcast input array from shape (320,100,3) into shape (100,100,3)
```
## Expected behavior

Success.

## Environment

```
python collect_env.py 
Collecting environment information...
PyTorch version: 1.6.0
Is debug build: False
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.3 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: version 3.14.0

Python version: 3.7 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: 10.1.243
GPU models and configuration: 
GPU 0: Quadro GV100
GPU 1: GeForce RTX 2080 Ti

Nvidia driver version: 455.28
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] efficientnet-pytorch==0.6.3
[pip3] numpy==1.19.1
[pip3] segmentation-models-pytorch==0.1.0
[pip3] torch==1.6.0
[pip3] torchvision==0.7.0
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               10.1.243             h6bb024c_0  
[conda] mkl                       2020.2                      256  
[conda] mkl-service               2.3.0            py37he904b0f_0  
[conda] mkl_fft                   1.2.0            py37h23d657b_0  
[conda] mkl_random                1.1.1            py37h0573a6f_0  
[conda] numpy                     1.19.1           py37hbc911f0_0  
[conda] numpy-base                1.19.1           py37hfa32c7d_0  
[conda] pytorch                   1.6.0           py3.7_cuda10.1.243_cudnn7.6.3_0    pytorch
[conda] torchvision               0.7.0                py37_cu101    pytorch
```

Tagging @bornaghotbi who contributed to this issue.