I created a similar example, and measure the allocated memory on the GPU, but before and after this list comprehension, there was no change in allocated and cached memories:
>>> import torch
>>> device = torch.device('cuda:0')
>>> torch.cuda.memory_allocated()
0
>>> torch.cuda.memory_cached()
0
>>> t = [torch.randn(100, 100).to(device) for i in range(10)]
>>> torch.cuda.memory_allocated()
404480
>>> torch.cuda.memory_cached()
1048576
>>> 
>>> 
>>> t = [v[0] for v in t]
>>> torch.cuda.memory_allocated()
404480
>>> torch.cuda.memory_cached()
1048576