Here is the output of the command:
Collecting environment information...
PyTorch version: 1.9.0+cu102
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Microsoft Windows 10 Home
GCC version: Could not collect
Clang version: Could not collect
CMake version: version 3.19.3
Libc version: N/A

Python version: 3.9 (64-bit runtime)
Python platform: Windows-10-10.0.19041-SP0
Is CUDA available: True
CUDA runtime version: 11.2.67
GPU models and configuration: GPU 0: GeForce RTX 2080 Ti
Nvidia driver version: 461.92
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.20.3
[pip3] torch==1.9.0+cu102
[pip3] torchaudio==0.9.0
[pip3] torchvision==0.10.0+cu102
[conda] Could not collect

And here is a snippet which could do the job. If it does not, you might have to do some fiddling to find the magic value for val - of course it depends on how much memory you have available on your GPU. You will have found the issue when the stack trace contains the actual print statement.
import torch

device = torch.device("cuda")
val = 17
while 1:
    x = torch.ones((int(val), ), dtype=torch.float16, device=device)
    print(x)
    val *= 1.1