Include torchax in torch_xla

.circleci/common.sh

@@ -106,18 +106,10 @@ function install_pre_deps_pytorch_xla() {
 }
 
 
+# TODO(https://github.com/pytorch/xla/issues/8934): Remove PyTorch usage of this function, then
+# remove this function from the script.
 function install_post_deps_pytorch_xla() {
-  # Install dependencies after we built torch_xla. This is due to installing
-  # those packages can potentially trigger `pip install torch_xla` if torch_xla
-  # is not detected in the system.
-
-  # Install JAX dependency since a few tests depend on it.
-  pip install 'torch_xla[pallas]' \
-  -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html \
-  -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
-
-  # TODO(https://github.com/pytorch/xla/issues/8831): Remove this when torchax is part of torch_xla.
-  pip install xla/torchax
+  true
 }
 
 function build_torch_xla() {

.github/workflows/_test.yml

@@ -128,13 +128,6 @@ jobs:
           set -x
 
           pip install expecttest unittest-xml-reporting
-          pip install torch_xla[pallas] \
-            -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html \
-            -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
-
-          # Install torchax
-          # TODO(https://github.com/pytorch/xla/issues/8831): Remove this when torchax is part of torch_xla.
-          pip install pytorch/xla/torchax
 
           if [[ ! -z "$RUN_BENCHMARK_TESTS" ]]; then
             pip install -r pytorch/xla/benchmarks/requirements.txt

.github/workflows/_test_requiring_torch_cuda.yml

@@ -91,9 +91,7 @@ jobs:
         shell: bash
         run: |
           set -x
-          pip install -U --pre jaxlib -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
-          pip install -U --pre jax-cuda12-pjrt jax-cuda12-plugin -f https://storage.googleapis.com/jax-releases/jax_cuda_plugin_nightly_releases.html
-          pip install -U --pre jax -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html
+          pip install -U --pre jax jaxlib "jax-cuda12-plugin[with_cuda]" jax-cuda12-pjrt -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html
         if: ${{ matrix.run_triton_tests }}
       - name: Install Triton
         shell: bash

.github/workflows/_tpu_ci.yml

@@ -23,14 +23,9 @@ jobs:
           pip install --upgrade pip
           pip install fsspec
           pip install rich
-          # Jax nightly is needed for pallas tests.
-          pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
+          # libtpu is needed for pallas tests.
           pip install torch_xla[tpu] -f https://storage.googleapis.com/libtpu-wheels/index.html -f https://storage.googleapis.com/libtpu-releases/index.html
           pip install --upgrade protobuf
-
-          # torchax is needed for call_jax tests.
-          # TODO(https://github.com/pytorch/xla/issues/8831): Remove this when torchax is part of torch_xla.
-          pip install pytorch/xla/torchax
       - name: Run Tests
         env:
           PJRT_DEVICE: TPU

.github/workflows/build_and_test.yml

@@ -4,16 +4,10 @@ on:
     branches:
       - master
       - r[0-9]+.[0-9]+
-    paths-ignore:
-      - 'experimental/**'
-      - 'torchax/**'
   push:
     branches:
       - master
       - r[0-9]+.[0-9]+
-    paths-ignore:
-      - 'experimental/**'
-      - 'torchax/**'
   workflow_dispatch:
 
 concurrency:

.github/workflows/torch_xla2.yml

@@ -3,14 +3,10 @@ on:
     branches:
       - master
       - r[0-9]+.[0-9]+
-    paths:
-      - 'torchax/**'
   push:
     branches:
       - master
       - r[0-9]+.[0-9]+
-    paths:
-      - 'torchax/**'
   workflow_dispatch:
 
 concurrency:

CONTRIBUTING.md

@@ -87,10 +87,6 @@ using either VS Code or a local container:
   pip install torch_xla[tpu] \
     -f https://storage.googleapis.com/libtpu-wheels/index.html \
     -f https://storage.googleapis.com/libtpu-releases/index.html
-  # Optional: if you're using custom kernels, install pallas dependencies
-  pip install torch_xla[pallas] \
-    -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html \
-    -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
   ```
 
 * If you are running on a TPU VM, ensure `torch` and `torch_xla` were built and 

README.md

@@ -29,11 +29,6 @@ To install PyTorch/XLA stable build in a new TPU VM:
 pip install torch~=2.6.0 'torch_xla[tpu]~=2.6.0' \
   -f https://storage.googleapis.com/libtpu-releases/index.html \
   -f https://storage.googleapis.com/libtpu-wheels/index.html
-
-# Optional: if you're using custom kernels, install pallas dependencies
-pip install 'torch_xla[pallas]' \
-  -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html \
-  -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
 ```
 
 To install PyTorch/XLA nightly build in a new TPU VM:
@@ -43,11 +38,6 @@ pip install --pre torch torchvision --index-url https://download.pytorch.org/whl
 pip install 'torch_xla[tpu] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev-cp310-cp310-linux_x86_64.whl' \
   -f https://storage.googleapis.com/libtpu-releases/index.html \
   -f https://storage.googleapis.com/libtpu-wheels/index.html
-
-# Optional: if you're using custom kernels, install pallas dependencies
-pip install 'torch_xla[pallas]' \
-  -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html \
-  -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
 ```
 
 ### C++11 ABI builds

scripts/build_developer.sh

@@ -21,16 +21,17 @@ cd ..
 if [ -d "vision" ]; then
   cd vision
   python3 setup.py develop
-  cd .. 
+  cd ..
 fi
 
 # Install torch_xla
 cd pytorch/xla
-pip uninstall torch_xla -y
+pip uninstall torch_xla torchax torch_xla2 -y
 
-# Optional: build the wheel.
+# Build the wheel too, which is useful for other testing purposes.
 python3 setup.py bdist_wheel
 
+# Link the source files for local development.
 python3 setup.py develop
 
 # libtpu is needed to talk to the TPUs. If TPUs are not present,
@@ -39,10 +40,5 @@ pip install torch_xla[tpu] \
   -f https://storage.googleapis.com/libtpu-wheels/index.html \
   -f https://storage.googleapis.com/libtpu-releases/index.html
 
-# Install Pallas dependencies
-pip install torch_xla[pallas] \
-  -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html \
-  -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
-
 # Test that the library is installed correctly.
-python3 -c 'import torch_xla as xla; print(xla.device())'
+python3 -c 'import torch_xla; print(torch_xla.devices()); import torchax; torchax.enable_globally()'

setup.py

@@ -53,6 +53,7 @@
 import distutils.ccompiler
 import distutils.command.clean
 import os
+import re
 import requests
 import shutil
 import subprocess
@@ -226,7 +227,7 @@ class BuildBazelExtension(build_ext.build_ext):
   def run(self):
     for ext in self.extensions:
       self.bazel_build(ext)
-    command.build_ext.build_ext.run(self)
+    command.build_ext.build_ext.run(self)  # type: ignore
 
   def bazel_build(self, ext):
     if not os.path.exists(self.build_temp):
@@ -260,17 +261,107 @@ def bazel_build(self, ext):
     shutil.copyfile(ext_bazel_bin_path, ext_dest_path)
 
 
+# Read in README.md for our long_description
+cwd = os.path.dirname(os.path.abspath(__file__))
+with open(os.path.join(cwd, "README.md"), encoding="utf-8") as f:
+  long_description = f.read()
+
+# Finds torch_xla and its subpackages
+packages_to_include = find_packages(include=['torch_xla*'])
+# Explicitly add torchax
+packages_to_include.extend(find_packages(where='torchax', include=['torchax*']))
+
+# Map the top-level 'torchax' package name to its source location
+torchax_dir = os.path.join(cwd, 'torchax')
+package_dir_mapping = {'torch_xla': os.path.join(cwd, 'torch_xla')}
+package_dir_mapping['torchax'] = os.path.join(torchax_dir, 'torchax')
+
+
 class Develop(develop.develop):
 
   def run(self):
+    # Build the C++ extension
     self.run_command("build_ext")
+
+    # Run the standard develop process first
+    # This installs dependencies, scripts, and importantly, creates an `.egg-link` file
     super().run()
 
+    # Replace the `.egg-link` with a `.pth` file.
+    self.link_packages()
+
+  def link_packages(self):
+    """
+    There are two mechanisms to install an "editable" package in Python: `.egg-link`
+    and `.pth` files. setuptools uses `.egg-link` by default. However, `.egg-link`
+    only supports linking a single directory containg one editable package.
+    This function removes the `.egg-link` file and generates a `.pth` file that can
+    be used to link multiple packages, in particular, `torch_xla` and `torchax`.
+
+    Note that this function is only relevant in the editable package development path
+    (`python setup.py develop`). Nightly and release wheel builds work out of the box
+    without egg-link/pth.
+    """
+    # Ensure paths like self.install_dir are set
+    self.ensure_finalized()
+
+    # Get the site-packages directory
+    target_dir = self.install_dir
+
+    # Remove the standard .egg-link file
+    # It's usually named based on the distribution name
+    dist_name = self.distribution.get_name()
+    egg_link_file = os.path.join(target_dir, dist_name + '.egg-link')
+    if os.path.exists(egg_link_file):
+      print(f"Removing default egg-link file: {egg_link_file}")
+      try:
+        os.remove(egg_link_file)
+      except OSError as e:
+        print(f"Warning: Could not remove {egg_link_file}: {e}")
+
+    # Create our custom .pth file with specific paths
+    cwd = os.path.dirname(__file__)
+    # Path containing 'torch_xla' package source: ROOT
+    path_for_torch_xla = os.path.abspath(cwd)
+    # Path containing 'torchax' package source: ROOT/torchax
+    path_for_torchax = os.path.abspath(os.path.join(cwd, 'torchax'))
+
+    paths_to_add = {path_for_torch_xla, path_for_torchax}
+
+    # Construct a suitable .pth filename (PEP 660 style is good practice)
+    version = self.distribution.get_version()
+    # Sanitize name and version for filename (replace runs of non-alphanumeric chars with '-')
+    sanitized_name = re.sub(r"[^a-zA-Z0-9.]+", "_", dist_name)
+    sanitized_version = re.sub(r"[^a-zA-Z0-9.]+", "_", version)
+    pth_filename = os.path.join(
+        target_dir, f"__editable_{sanitized_name}_{sanitized_version}.pth")
+
+    # Ensure site-packages exists
+    os.makedirs(target_dir, exist_ok=True)
+
+    # Write the paths to the .pth file, one per line
+    with open(pth_filename, "w", encoding='utf-8') as f:
+      for path in sorted(paths_to_add):
+        f.write(path + "\n")
+
+
+def _get_jax_install_requirements():
+  if not USE_NIGHTLY:
+    # Stable versions of JAX can be directly installed from PyPI.
+    return [
+        f'jaxlib=={_jaxlib_version}',
+        f'jax=={_jax_version}',
+    ]
+
+  # Install nightly JAX libraries from the JAX package registries.
+  jax = f'jax @ https://storage.googleapis.com/jax-releases/nightly/jax/jax-{_jax_version}-py3-none-any.whl'
+  jaxlib = []
+  for python_minor_version in [9, 10, 11]:
+    jaxlib.append(
+        f'jaxlib @ https://storage.googleapis.com/jax-releases/nightly/nocuda/jaxlib-{_jaxlib_version}-cp3{python_minor_version}-cp3{python_minor_version}-manylinux2014_x86_64.whl ; python_version == "3.{python_minor_version}"'
+    )
+  return [jax] + jaxlib
 
-# Read in README.md for our long_description
-cwd = os.path.dirname(os.path.abspath(__file__))
-with open(os.path.join(cwd, "README.md"), encoding="utf-8") as f:
-  long_description = f.read()
 
 setup(
     name=os.environ.get('TORCH_XLA_PACKAGE_NAME', 'torch_xla'),
@@ -297,7 +388,8 @@ def run(self):
         "Programming Language :: Python :: 3",
     ],
     python_requires=">=3.8.0",
-    packages=find_packages(include=['torch_xla*']),
+    packages=packages_to_include,
+    package_dir=package_dir_mapping,
     ext_modules=[
         BazelExtension('//:_XLAC.so'),
         BazelExtension('//:_XLAC_cuda_functions.so'),
@@ -310,6 +402,8 @@ def run(self):
         # importlib.metadata backport required for PJRT plugin discovery prior
         # to Python 3.10
         'importlib_metadata>=4.6;python_version<"3.10"',
+        # Some torch operations are lowered to HLO via JAX.
+        *_get_jax_install_requirements(),
     ],
     package_data={
         'torch_xla': ['lib/*.so*',],
@@ -331,6 +425,8 @@ def run(self):
             f'libtpu=={_libtpu_version}',
             'tpu-info',
         ],
+        # As of https://github.com/pytorch/xla/pull/8895, jax is always a dependency of torch_xla.
+        # However, this no-op extras_require entrypoint is left here for backwards compatibility.
         # pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
         'pallas': [f'jaxlib=={_jaxlib_version}', f'jax=={_jax_version}'],
     },

test/tpu/xla_test_job.yaml

@@ -43,7 +43,6 @@ spec:
     - |
       pip install expecttest==0.1.6
       pip install rich
-      pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
 
       cd /src/pytorch/xla
     volumeMounts:

torchax/README.md

@@ -1,7 +1,7 @@
 # torchax: Running PyTorch on TPU
 
-**torchax!** is a backend for PyTorch, allowing users to run
-PyTorch on Google CloudTPUs. **torchax!** is also a library for providing
+**torchax** is a backend for PyTorch, allowing users to run
+PyTorch on Google CloudTPUs. **torchax** is also a library for providing
 graph-level interoperability between PyTorch and Jax.
 
 This means, with **torchax** you can:
@@ -133,7 +133,7 @@ Then, a `jax` device will be available to use
 
 ```python
 inputs = torch.randn(3, 3, 28, 28, device='jax')
-m = MyModel()
+m = MyModel().to('jax')
 res = m(inputs)
 print(type(res))  # outputs torchax.tensor.Tensor
 ```
@@ -220,13 +220,15 @@ then the subsequent computation with inputs of same shape will be fast.
 
 # Citation:
 
+```
 @software{torchax,
   author = {Han Qi, Chun-nien Chan, Will Cromar, Manfei Bai, Kevin Gleanson},
   title = {torchax: PyTorch on TPU and Jax interoperability},
   url = {https://github.com/pytorch/xla/tree/master/torchax}
   version = {0.0.4},
   date = {2025-02-24},
 }
+```
 
 # Maintainers & Contributors:
 
@@ -238,6 +240,7 @@ fellow Googlers using [Google's 20% project policy](https://ebsedu.org/blog/goog
 
 Here is the full list of contributors by 2025-02-25.
 
+```
 Han Qi (qihqi), Pytorch / XLA
 Manfei Bai (manfeibai), Pytorch / XLA
 Will Cromar (will-cromar), Meta
@@ -273,4 +276,5 @@ Tianqi Fan (tqfan28), Google(20%)
 Jim Lin (jimlinntu), Google(20%)
 Fanhai Lu (FanhaiLu1), Google Cloud
 DeWitt Clinton (dewitt), Google PyTorch
-Aman Gupta (aman2930) , Google(20%)
+Aman Gupta (aman2930) , Google(20%)
+```

torchax/pyproject.toml

@@ -41,7 +41,7 @@ path = "torchax/__init__.py"
 
 [project.optional-dependencies]
 cpu = ["jax[cpu]>=0.4.30", "jax[cpu]"]
-# Add libtpu index `-f https://storage.googleapis.com/libtpu-releases/index.html`
+# Add libtpu index `-f https://storage.googleapis.com/libtpu-wheels/index.html -f https://storage.googleapis.com/libtpu-releases/index.html`
 tpu = ["jax[cpu]>=0.4.30", "jax[tpu]"]
 cuda = ["jax[cpu]>=0.4.30", "jax[cuda12]"]
 odml = ["jax[cpu]>=0.4.30", "jax[cpu]"]