AdministrativeCar545

I have an 8-GPU machine and I usually run 8 independent training jobs, one per GPU.

For GPUs this is easy:

CUDA_VISIBLE_DEVICES=0 python train.py
CUDA_VISIBLE_DEVICES=1 python train.py
...

Each job only sees one GPU.

The problem is CPU usage. Since I do not isolate CPU resources, every job can see all CPU cores. Then dataloaders / PyTorch workers may spawn lots of threads, and the 8 jobs start fighting for CPU.

I know I can manually tune things in code, e.g. num_workers, OMP_NUM_THREADS, MKL_NUM_THREADS, etc. But I am looking for something more like CUDA_VISIBLE_DEVICES for CPUs: a simple and clean way to assign each job a fixed subset of CPU cores.

What is the

Hi there, I have ChatGPT Plus subscription and recently have switched the model from GPT 5.4 to 5.5. However I found that the weekly limit & 5h limit are significantly fast reached. Is that bcz OpenAI measures usage beased on the models behind?

I found this: https://help.openai.com/en/articles/20001106-codex-rate-card?utm_source=chatgpt.com

https://preview.redd.it/nz843p7dnnxg1.png?width=1584&format=png&auto=webp&s=a268ea9809130e2167ba75aabb0d8cc9cc4df291

Hi there, I recently got a new UC Davis account through TAF, and I’m trying to set up Duo.

The problem is that when I go to the Duo setup / device manager page, it keeps redirecting me to the UC Davis CAS login page. After I enter my username and password, it sometimes says I’ve successfully logged out, and then if I try again it says it doesn’t know where to redirect me. Eventually I get:

So I’m basically stuck in a loop where I need Duo, but I can’t complete Duo enrollment.

Since this is a newly created TAF account, I’m wondering whether this is normal for a new account, or whether something is broken and I need to contact IT.

Has anyone run into this before?

Hi all,

I'm currently working on an offline RL / world model project and trying to get Atari gameplay data (observations, actions, rewards, etc.). The only dataset I could find is D4RL-Atari, which looks perfect for my needs.

However, this library requires downloading data from a GCS bucket which is now inaccessible (See https://github.com/takuseno/d4rl-atari/issues/19#issue-2968016846), making this library unavailable. Does anyone know:

• If there's an alternative mirror or source for this dataset?
• If the authors or others have a backup?
• Any other public offline Atari datasets in similar format (frame + action + reward + terminal)?

I'm trying to run a reinforcement learning environment on a remote Ubuntu server, and I need to manually interact with the game window rendered via PyGame. The idea is to run the environment on the server and forward the display to my macOS machine using X11. I'm on an Apple Silicon (M1) Mac.

I'm currently using XQuartz for X11 forwarding. I can connect via SSH with -X or -Y and basic X11 apps like xeyes display fine. However, when PyGame tries to open its window, I get the following OpenGL error when checking glxinfo:

name of display: localhost:10.0

libGL error: No matching fbConfigs or visuals found

libGL error: failed to load driver: swrast

display: localhost:10 screen:

Hi all,

recently I'm into a unsupervised learning project where ViT is used and attention weights of the last attention layer are needed for some visualizations. I found my it very hard to scale up with image size.

Suppose each image is square and has height/width L, then the image token sequence has length N=L^2, and each attention weights matrix is of size (N, N) since each image token attends to each image token (here I omit the CLS token). As a result, the space complexity, i.e., VRAM usage, is about O(N^2) = O(L^4), and the time complexity is also O(L^4).

That being said, it's a fourth-order complexity w.r.t. image height/width. I know that libraries like flash attention can o

Hi there,

I've been working with DinoV2 and noticed something strange: extracting attention weights is dramatically slower than getting CLS token embeddings, even though they both require almost the same forward pass through the model.

I'm using the official DinoV2 implementation (https://github.com/facebookresearch/dinov2). Here's my benchmark result:

```
Input tensor shape: Batch=10, Channels=3, Height=896, Width=896

Patch size: 14

Token embedding dimension: 384

Number of patches of each image: 4096

Attention Map Generation Performance Metrics:

Time: 5326.52 ms VRAM: Current usage: 2444.27 MB VRAM: Peak increment: 8.12 MB

Embedding Generation Performance Metrics: Time:

Hey there,

I'm currently working with DreamerV3 on several control tasks, including DeepMind Control Suite's walker_walk. I've noticed something interesting that I'm hoping the community might have insights on.

**Issue**: Even after both my world model and policy seem to have converged (based on their respective training losses), I still see fluctuations in the episode scores during policy learning.

I understand that DreamerV3 follows the DYNA scheme (from Sutton's DYNA paper), where the world model and policy are trained in parallel. My expectation was that once the world model has converged to an accurate representation of the environment, the policy performance should stabili

Hey Aggies!
I was wondering if anyone has experience traveling from UC Davis to UC San Diego (or just San Diego in general) over a weekend — like leaving Friday and coming back Sunday. I don’t have a car, so I’m trying to figure out if this is realistically doable using public transportation or flights.

I shared my situation before: Eye Irritation and Red Eye.

Now, my allergy test shows IgE > 1000, with multiple allergies (dust mites, cockroach, pollen, etc.). I’ve used Olopatadine daily for 3 months—it helps, but I still feel dry eye and discomfort every day. I also wear RGP lenses.

Weirdly, I don’t have typical allergy symptoms—just eye issues and more nasal discharge.

I plan to see a doctor. Any advice on treatment or what else this could be?

Hi all, I have a task to implement a model called "Dinov2 with registers" in flax. Hugginface already had a torch version for this, but there's no flax version yet. I think that once I implemented a flax version, then I can use it without the need of providing pretrained weights due to the use_pt=True api provided by hugginface. The problem is how. I have no experience of translating such a complex torch model to flax, ChatGPT can't solve this.

( I know hugginface has both torch and flax implementations of "Dinov2". But that's a worse model compared to the one with registers.)

Thanks for your advice!

Recently the school updated Duo authentication for some aggies. Please follow the instruction of this llink:

https://movetoduo.ucdavis.edu/

to update ur Duo :)

Sorry guys, I just can't hold it in. The things happening in the world—no need to say what, you all know—are breaking my heart. How did we end up here? Just ten years ago, it felt like we were moving toward a brighter, more united future, a world where people believed in peace and understanding. But that hope now feels completely shattered. I can’t stop feeling sad for all the pain and suffering people are going through.

Hi all,

While learning reinforcement learning, I've been struggling with the math, especially expectation notation. For example, the value function is often written as:

$$

V^\pi(s)=\mathbb{E}_\pi\left\{R_t \mid s_t=s\right\}=\mathbb{E}_\pi\left\{\sum_{k=0}^{\infty} \gamma^k r_{t+k+1} \mid s_t=s\right\}

$$

What exactly does $\mathbb{E}_\pi$ mean? I thought the subscript should be a probability distribution or random variable, but $\pi$ is a policy (a function).

This confusion also comes up with trajectory definitions like:

$$

P(\tau \mid \pi)=\rho_0\left(s_0\right) \prod_{t=0}^{T-1} P\left(s_{t+1} \mid s_t, a_t\right) \pi\le