Update 2.3 readme (#6957)

pytorch · Apr 24, 2024 · 8c33979 · 8c33979
1 parent 7674030
commit 8c33979
Showing 1 changed file with 3 additions and 155 deletions.
diff --git a/README.md b/README.md
@@ -14,14 +14,7 @@ TPUs](https://cloud.google.com/tpu/). You can try it right now, for free, on a
 single Cloud TPU VM with
 [Kaggle](https://www.kaggle.com/discussions/product-feedback/369338)!
 
-Take a look at one of our [Kaggle
-notebooks](https://github.com/pytorch/xla/tree/master/contrib/kaggle) to get
-started:
-
-* [Stable Diffusion with PyTorch/XLA
-  2.0](https://github.com/pytorch/xla/blob/master/contrib/kaggle/pytorch-xla-2-0-on-kaggle.ipynb)
-* [Distributed PyTorch/XLA
-  Basics](https://github.com/pytorch/xla/blob/master/contrib/kaggle/distributed-pytorch-xla-basics-with-pjrt.ipynb)
+Please find tutorials on our [GitHub page](https://github.com/pytorch/xla) for the latest release.
 
 ## Installation
 
@@ -148,153 +141,8 @@ Our comprehensive user guides are available at:
 
 ## Available docker images and wheels
 
-### Python packages
-
-PyTorch/XLA releases starting with version r2.1 will be available on PyPI. You
-can now install the main build with `pip install torch_xla`. To also install the
-Cloud TPU plugin, install the optional `tpu` dependencies:
-
-```
-pip install torch_xla[tpu] -f https://storage.googleapis.com/libtpu-releases/index.html
-```
-
-GPU, XRT (legacy runtime), and nightly builds are available in our public GCS
-bucket.
-
-| Version | Cloud TPU/GPU VMs Wheel |
-| --- | ----------- |
-| 2.2 (Python 3.8) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.2.0-cp38-cp38-manylinux_2_28_x86_64.whl` |
-| 2.2 (Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.2.0-cp310-cp310-manylinux_2_28_x86_64.whl` |
-| 2.2 (CUDA 12.1 + Python 3.8) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/12.1/torch_xla-2.2.0-cp38-cp38-manylinux_2_28_x86_64.whl` |
-| 2.2 (CUDA 12.1 + Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/12.1/torch_xla-2.2.0-cp310-cp310-manylinux_2_28_x86_64.whl` |
-| nightly (Python 3.8) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-nightly-cp38-cp38-linux_x86_64.whl` |
-| nightly (Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-nightly-cp310-cp310-linux_x86_64.whl` |
-| nightly (CUDA 12.1 + Python 3.8) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/12.1/torch_xla-nightly-cp38-cp38-linux_x86_64.whl` |
-
-<details>
-
-<summary>older versions</summary>
-
-| Version | Cloud TPU VMs Wheel |
-|---------|-------------------|
-| 2.1 (XRT + Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/xrt/tpuvm/torch_xla-2.1.0%2Bxrt-cp310-cp310-manylinux_2_28_x86_64.whl` |
-| 2.1 (Python 3.8) | `https://storage.googleapis.com/tpu-pytorch/wheels/tpuvm/torch_xla-2.1-cp38-cp38-linux_x86_64.whl` |
-| 2.0 (Python 3.8) | `https://storage.googleapis.com/tpu-pytorch/wheels/tpuvm/torch_xla-2.0-cp38-cp38-linux_x86_64.whl` |
-| 1.13 | `https://storage.googleapis.com/tpu-pytorch/wheels/tpuvm/torch_xla-1.13-cp38-cp38-linux_x86_64.whl` |
-| 1.12 | `https://storage.googleapis.com/tpu-pytorch/wheels/tpuvm/torch_xla-1.12-cp38-cp38-linux_x86_64.whl` |
-| 1.11 | `https://storage.googleapis.com/tpu-pytorch/wheels/tpuvm/torch_xla-1.11-cp38-cp38-linux_x86_64.whl` |
-| 1.10 | `https://storage.googleapis.com/tpu-pytorch/wheels/tpuvm/torch_xla-1.10-cp38-cp38-linux_x86_64.whl` |
-
-<br/>
-
-Note: For TPU Pod customers using XRT (our legacy runtime), we have custom
-wheels for `torch` and `torch_xla` at
-`https://storage.googleapis.com/tpu-pytorch/wheels/xrt`.
-
-| Package | Cloud TPU VMs Wheel (XRT on Pod, Legacy Only) |
-| --- | ----------- |
-| torch_xla | `https://storage.googleapis.com/pytorch-xla-releases/wheels/xrt/tpuvm/torch_xla-2.1.0%2Bxrt-cp310-cp310-manylinux_2_28_x86_64.whl` |
-| torch | `https://storage.googleapis.com/pytorch-xla-releases/wheels/xrt/tpuvm/torch-2.1.0%2Bxrt-cp310-cp310-linux_x86_64.whl` |
-
-<br/>
-
-| Version | GPU Wheel + Python 3.8 |
-| --- | ----------- |
-| 2.1+ CUDA 11.8 | `https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/11.8/torch_xla-2.1.0-cp38-cp38-manylinux_2_28_x86_64.whl` |
-| 2.0 + CUDA 11.8 | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/118/torch_xla-2.0-cp38-cp38-linux_x86_64.whl` |
-| 2.0 + CUDA 11.7 | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/117/torch_xla-2.0-cp38-cp38-linux_x86_64.whl` |
-| 1.13 | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/112/torch_xla-1.13-cp38-cp38-linux_x86_64.whl` |
-| nightly + CUDA 12.0 >= 2023/06/27| `https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/12.0/torch_xla-nightly-cp38-cp38-linux_x86_64.whl` |
-| nightly + CUDA 11.8 <= 2023/04/25| `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/118/torch_xla-nightly-cp38-cp38-linux_x86_64.whl` |
-| nightly + CUDA 11.8 >= 2023/04/25| `https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/11.8/torch_xla-nightly-cp38-cp38-linux_x86_64.whl` |
-
-<br/>
-
-| Version | GPU Wheel + Python 3.7 |
-| --- | ----------- |
-| 1.13 | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/112/torch_xla-1.13-cp37-cp37m-linux_x86_64.whl` |
-| 1.12 | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/112/torch_xla-1.12-cp37-cp37m-linux_x86_64.whl` |
-| 1.11 | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/112/torch_xla-1.11-cp37-cp37m-linux_x86_64.whl` |
-| nightly | `https://storage.googleapis.com/tpu-pytorch/wheels/cuda/112/torch_xla-nightly-cp37-cp37-linux_x86_64.whl` |
-
-<br/>
-
-| Version | Colab TPU Wheel |
-| --- | ----------- |
-| 2.0 | `https://storage.googleapis.com/tpu-pytorch/wheels/colab/torch_xla-2.0-cp310-cp310-linux_x86_64.whl` |
-
-You can also add `+yyyymmdd` after `torch_xla-nightly` to get the nightly wheel
-of a specified date. To get the companion pytorch and torchvision nightly wheel,
-replace the `torch_xla` with `torch` or `torchvision` on above wheel links.
-
-#### Installing libtpu (before PyTorch/XLA 2.0)
-
-For PyTorch/XLA release r2.0 and older and when developing PyTorch/XLA, install
-the `libtpu` pip package with the following command:
-
-```
-pip3 install torch_xla[tpuvm]
-```
-
-This is only required on Cloud TPU VMs.
-
-</details>
-
-### Docker
-
-| Version | Cloud TPU VMs Docker |
-| --- | ----------- |
-| 2.2 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.2.0_3.10_tpuvm` |
-| 2.1 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.1.0_3.10_tpuvm` |
-| 2.0 | `gcr.io/tpu-pytorch/xla:r2.0_3.8_tpuvm` |
-| 1.13 | `gcr.io/tpu-pytorch/xla:r1.13_3.8_tpuvm` |
-| nightly python | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.10_tpuvm` |
-
-<br/>
-
-| Version | GPU CUDA 12.1 Docker |
-| --- | ----------- |
-| 2.2 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.2.0_3.10_cuda_12.1` |
-| 2.1 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.1.0_3.10_cuda_12.1` |
-| nightly | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.8_cuda_12.1` |
-| nightly at date | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.8_cuda_12.1_YYYYMMDD` |
-
-<br/>
-
-| Version | GPU CUDA 11.8 + Docker |
-| --- | ----------- |
-| 2.1 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.1.0_3.10_cuda_11.8` |
-| 2.0 | `gcr.io/tpu-pytorch/xla:r2.0_3.8_cuda_11.8` |
-| nightly | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.8_cuda_11.8` |
-| nightly at date | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.8_cuda_11.8_YYYYMMDD` |
-
-<br/>
-
-<details>
-
-<summary>older versions</summary>
-
-| Version | GPU CUDA 11.7 + Docker |
-| --- | ----------- |
-| 2.0 | `gcr.io/tpu-pytorch/xla:r2.0_3.8_cuda_11.7` |
-
-<br/>
-
-| Version | GPU CUDA 11.2 + Docker |
-| --- | ----------- |
-| 1.13 | `gcr.io/tpu-pytorch/xla:r1.13_3.8_cuda_11.2` |
-
-<br/>
-
-| Version | GPU CUDA 11.2 + Docker |
-| --- | ----------- |
-| 1.13 | `gcr.io/tpu-pytorch/xla:r1.13_3.7_cuda_11.2` |
-| 1.12 | `gcr.io/tpu-pytorch/xla:r1.12_3.7_cuda_11.2` |
-
-</details>
-
-To run on [compute instances with
-GPUs](https://cloud.google.com/compute/docs/gpus/create-vm-with-gpus).
+For all builds and all versions of `torch-xla`, see our main [GitHub
+README](https://github.com/pytorch/xla).
 
 ## Troubleshooting