Skip to content

Minimum hardware requirement to prevent CUDA out of memory #73

Description

@jchai01

Trying to run this on a laptop GPU
Model: Dell Precision 3480
GPU: NVIDIA RTX A500 Laptop GPU
VRAM: 4GB
OS: Ubuntu 22

Getting this error despite trying various flags from the readme, as well as #64

torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 16.00 MiB. GPU 0 has a total capacity of 3.68 GiB of which 27.44 MiB is free. Including non-PyTorch memory, this process has 2.83 GiB memory in use. Of the allocated memory 2.75 GiB is allocated by PyTorch, and 12.77 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

What is the minimum hardware required to get a decent result from the demo?
If #64 were to work, is ~21 images/frames a limit I have to work with using a laptop GPU?

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type
    No fields configured for issues without a type.

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions