Ops trax pod9/11/2023 Step 2: within a few hours, you'll likely receive an email saying "Congratulations! You have access to for the next 30 days. Though I do have to consciously suppress the urge to call 'em TFRC anyway.) (Ever hear of TFRC? Well, TRC is their new name. Step 1: apply for the TPU Research Cloud (TRC):.By now, you've no doubt been hearing stuff like, "These TPU VM things are pretty fast now. I felt like writing a small guide for all the curious ML devs. "How do I get started with Jax on TPU VMs?" tree_map( lambda x: x, params), device = cpu_device) device_put( total_grad, device = cpu_device)Ĭpu_params = jax. jit, static_argnums = 3) def opt_jit( grad_acc, opt_state, params, optimizer): Note that Google's official MLPerf benchmarks uses this technique for resnet training: partial( jax. It's just like running ops on one of the TPU's cores, except it corresponds to the TPU's CPU instead. This corresponds to the TPU's /device:CPU:0 device, which doesn't seem special. So, given that using 300 GB of memory is one of the best features that TPUs have to offer, is there anything that can be done to support this feature in Jax?Īll that needs to be done to support it is to be able to execute ops on the TPU's CPU. Here's an HN thread where I illustrate how the TPU can use 300GB of memory: Īnd a simple notebook that fine-tunes GPT-2 1.5B using a TPUv2 (which is quite impossible if you were limited to only 8GB): I myself discovered the feature by accident. In fact, the 300 GB limit is so high that people often refuse to believe that this is even possible. As far as I'm concerned, it's one of the best features of TPUs. 300 GB is far, far higher than the TPU's normal limit. When you run ops on the TPU's CPU, you have access to up to 300 GB of memory(!) without running into errors. It's as easy as running tf.device(None): # ops go here. I do this all the time for fine-tuning GPT-2 1.5B. It's a piece of hardware that has a CPU, RAM, and 8 cores. I think there might be some confusion in this thread.Ī TPU isn't just a piece of hardware with 8 cores.
0 Comments
Leave a Reply.AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |