torch.cuda.memory_reserved() will return the allocated and cached memory, which might be higher, e.g. if you are using cudnn.backend.benchmark=True (and cudnn would profile more kernels, if they are available for mixed-precision).
To check the allocated memory, you could use torch.cuda.memory_allocated().