Merge branch 'main' of https://github.com/SmallDoges/flash-dmattn

Author: algo-home

.github/workflows/publish.yml

@@ -45,7 +45,7 @@ jobs:
         # manylinux docker image, but I haven't figured out how to install CUDA on manylinux.
         os: [ubuntu-22.04, ubuntu-22.04-arm]
         python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
-        torch-version: ["2.4.0", "2.5.1", "2.6.0", "2.7.1", "2.8.0"]
+        torch-version: ["2.5.1", "2.6.0", "2.7.1", "2.8.0"]
         cuda-version: ["12.9.1"]
         # We need separate wheels that either uses C++11 ABI (-D_GLIBCXX_USE_CXX11_ABI) or not.
         # Pytorch wheels currently don't use it, but nvcr images have Pytorch compiled with C++11 ABI.
@@ -60,6 +60,9 @@ jobs:
           # Pytorch < 2.5 does not support Python 3.13
           - torch-version: "2.4.0"
             python-version: "3.13"
+          - torch-version: "2.5.1"
+            python-version: "3.13"
+            os: ubuntu-22.04-arm
     uses: ./.github/workflows/_build.yml
     with:
       runs-on: ${{ matrix.os }}

setup.py

@@ -37,6 +37,10 @@
 
 PACKAGE_NAME = "flash_dmattn"
 
+BASE_WHEEL_URL = (
+    "https://github.com/SmallDoges/flash-dmattn/releases/download/{tag_name}/{wheel_name}"
+)
+
 # FORCE_BUILD: Force a fresh build locally, instead of attempting to find prebuilt wheels
 # SKIP_CUDA_BUILD: Intended to allow CI to use a simple `python setup.py sdist` run to copy over raw files, without any cuda compilation
 # Also useful when user only wants Triton/Flex backends without CUDA compilation
@@ -307,6 +311,67 @@ def get_package_version():
         return str(public_version)
 
 
+def get_wheel_url():
+    torch_version_raw = parse(torch.__version__)
+    python_version = f"cp{sys.version_info.major}{sys.version_info.minor}"
+    platform_name = get_platform()
+    flash_version = get_package_version()
+    torch_version = f"{torch_version_raw.major}.{torch_version_raw.minor}"
+    cxx11_abi = str(torch._C._GLIBCXX_USE_CXX11_ABI).upper()
+
+    # Determine the version numbers that will be used to determine the correct wheel
+    # We're using the CUDA version used to build torch, not the one currently installed
+    # _, cuda_version_raw = get_cuda_bare_metal_version(CUDA_HOME)
+    torch_cuda_version = parse(torch.version.cuda)
+    # For CUDA 11, we only compile for CUDA 11.8, and for CUDA 12 we only compile for CUDA 12.3
+    # to save CI time. Minor versions should be compatible.
+    torch_cuda_version = parse("11.8") if torch_cuda_version.major == 11 else parse("12.3")
+    # cuda_version = f"{cuda_version_raw.major}{cuda_version_raw.minor}"
+    cuda_version = f"{torch_cuda_version.major}"
+
+    # Determine wheel URL based on CUDA version, torch version, python version and OS
+    wheel_filename = f"{PACKAGE_NAME}-{flash_version}+cu{cuda_version}torch{torch_version}cxx11abi{cxx11_abi}-{python_version}-{python_version}-{platform_name}.whl"
+
+    wheel_url = BASE_WHEEL_URL.format(tag_name=f"v{flash_version}", wheel_name=wheel_filename)
+
+    return wheel_url, wheel_filename
+
+
+class CachedWheelsCommand(_bdist_wheel):
+    """
+    The CachedWheelsCommand plugs into the default bdist wheel, which is ran by pip when it cannot
+    find an existing wheel (which is currently the case for all flash attention installs). We use
+    the environment parameters to detect whether there is already a pre-built version of a compatible
+    wheel available and short-circuits the standard full build pipeline.
+    """
+
+    def run(self):
+        if FORCE_BUILD:
+            return super().run()
+
+        wheel_url, wheel_filename = get_wheel_url()
+        print("Guessing wheel URL: ", wheel_url)
+        try:
+            urllib.request.urlretrieve(wheel_url, wheel_filename)
+
+            # Make the archive
+            # Lifted from the root wheel processing command
+            # https://github.com/pypa/wheel/blob/cf71108ff9f6ffc36978069acb28824b44ae028e/src/wheel/bdist_wheel.py#LL381C9-L381C85
+            if not os.path.exists(self.dist_dir):
+                os.makedirs(self.dist_dir)
+
+            impl_tag, abi_tag, plat_tag = self.get_tag()
+            archive_basename = f"{self.wheel_dist_name}-{impl_tag}-{abi_tag}-{plat_tag}"
+
+            wheel_path = os.path.join(self.dist_dir, archive_basename + ".whl")
+            print("Raw wheel path", wheel_path)
+            os.rename(wheel_filename, wheel_path)
+        except (urllib.error.HTTPError, urllib.error.URLError):
+            print("Precompiled wheel not found. Building from source...")
+            # If the wheel could not be downloaded, build from source
+            super().run()
+
+
 class NinjaBuildExtension(BuildExtension):
     def __init__(self, *args, **kwargs) -> None:
         # do not override env MAX_JOBS if already exists
@@ -329,7 +394,9 @@ def __init__(self, *args, **kwargs) -> None:
 
 setup(
     ext_modules=ext_modules,
-    cmdclass={"build_ext": NinjaBuildExtension}
+    cmdclass={"bdist_wheel": CachedWheelsCommand, "build_ext": NinjaBuildExtension}
     if ext_modules
-    else {},
+    else {
+        "bdist_wheel": CachedWheelsCommand,
+    },
 )