Clean up setup.py (#128)

* ignore more things

* update setup.py

* init pyproject.toml

* update README

* remove section seperations

* remove unused variable

* add docstring

* read version from megablocks/__init__.py

* fix reading repo version

* add type hints

* add classifiers, better long-description

* update url

* exclude more packages

* add python_requires

* update

* use Composer's .gitignore

* use Composer's pyproject.toml + my changes

* remove my stk fork

* remove composer specific

* better error msg

* fix typo

* add correct versions of stanford-stk, grouped_gemm; add packaging

* test in my GA

* use my fork for testing

* __init__.py only has __version

* change GA to defaults

* restore __init__.py

* update readme

* update readme

README.md

@@ -22,9 +22,9 @@ NOTE: This assumes you have `numpy` and `torch` installed.
 
 Installing `megablocks[gg]` enables dMoE computation with grouped GEMM. This feature is enabled by setting the `mlp_impl` argument to `grouped`. This is currently our recommended path for Hopper-generation GPUs.
 
-Installing `megablocks[dev]` allows you to contribute to MegaBlocks and test locally. Installing `megablocks[testing]` allows you to test via Github Actions.
+Installing `megablocks[dev]` allows you to contribute to MegaBlocks and test locally. Installing `megablocks[testing]` allows you to test via Github Actions. If you've installed megablocks[dev], you can run pre-commit install to configure the pre-commit hook to automatically format the code.
 
-MegaBlocks can be installed with all dependencies via the `megablocks[all]` package.
+MegaBlocks can be installed with all dependencies (except for `testing`) via the `megablocks[all]` package.
 
 # :steam_locomotive: Usage
 

megablocks/_version.py

@@ -0,0 +1,6 @@
+# Copyright 2022 MegaBlocks Composer authors
+# SPDX-License-Identifier: Apache-2.0
+
+"""The MegaBlocks Version."""
+
+__version__ = '0.5.1'

setup.py

@@ -1,40 +1,77 @@
+# Copyright 2024 MosaicML MegaBlocks authors
+# SPDX-License-Identifier: Apache-2.0
+
+"""MegaBlocks package setup."""
+
 import os
+import warnings
+from typing import Any, Dict, Mapping
 
-import torch
 from setuptools import find_packages, setup
-from torch.utils.cpp_extension import BuildExtension, CUDAExtension
 
-if os.environ.get("TORCH_CUDA_ARCH_LIST"):
-    # Let PyTorch builder to choose device to target for.
-    device_capability = ""
-else:
-    device_capability = torch.cuda.get_device_capability()
-    device_capability = f"{device_capability[0]}{device_capability[1]}"
 
-nvcc_flags = [
-    "--ptxas-options=-v",
-    "--optimize=2",
-]
-if device_capability:
-    nvcc_flags.append(
-        f"--generate-code=arch=compute_{device_capability},code=sm_{device_capability}"
-    )
-
-ext_modules = [
-    CUDAExtension(
-        "megablocks_ops",
-        ["csrc/ops.cu"],
-        include_dirs=["csrc"],
-        extra_compile_args={"cxx": ["-fopenmp"], "nvcc": nvcc_flags},
-    )
+# We require torch in setup.py to build cpp extensions "ahead of time"
+# More info here: # https://pytorch.org/tutorials/advanced/cpp_extension.html
+try:
+    import torch
+    from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension,
+                                           CUDAExtension,)
+except ModuleNotFoundError as e:
+    raise ModuleNotFoundError(
+        "No module named 'torch'. `torch` is required to install `MegaBlocks`."
+    ) from e
+
+
+_PACKAGE_NAME = 'megablocks'
+_PACKAGE_DIR = 'megablocks'
+_REPO_REAL_PATH = os.path.dirname(os.path.realpath(__file__))
+_PACKAGE_REAL_PATH = os.path.join(_REPO_REAL_PATH, _PACKAGE_DIR)
+
+# Read the package version
+# We can't use `.__version__` from the library since it's not installed yet
+version_path = os.path.join(_PACKAGE_REAL_PATH, '_version.py')
+with open(version_path, encoding='utf-8') as f:
+    version_globals: Dict[str, Any] = {}
+    version_locals: Mapping[str, object] = {}
+    content = f.read()
+    exec(content, version_globals, version_locals)
+    repo_version = version_locals['__version__']
+
+
+with open('README.md', 'r', encoding='utf-8') as fh:
+    long_description = fh.read()
+
+# Hide the content between <!-- SETUPTOOLS_LONG_DESCRIPTION_HIDE_BEGIN --> and
+# <!-- SETUPTOOLS_LONG_DESCRIPTION_HIDE_END --> tags in the README
+while True:
+    start_tag = '<!-- SETUPTOOLS_LONG_DESCRIPTION_HIDE_BEGIN -->'
+    end_tag = '<!-- SETUPTOOLS_LONG_DESCRIPTION_HIDE_END -->'
+    start = long_description.find(start_tag)
+    end = long_description.find(end_tag)
+    if start == -1:
+        assert end == -1, 'there should be a balanced number of start and ends'
+        break
+    else:
+        assert end != -1, 'there should be a balanced number of start and ends'
+        long_description = long_description[:start] + \
+            long_description[end + len(end_tag):]
+
+
+classifiers = [
+    'Programming Language :: Python :: 3',
+    'Programming Language :: Python :: 3.9',
+    'Programming Language :: Python :: 3.10',
+    'Programming Language :: Python :: 3.11',
+    'License :: OSI Approved :: BSD License',
+    'Operating System :: Unix',
 ]
 
 install_requires = [
     'numpy>=1.21.5,<2.1.0',
+    'packaging>=21.3.0,<24.2',
     'torch>=2.3.0,<2.4',
     'triton>=2.1.0',
     'stanford-stk @ git+https://[email protected]/stanford-futuredata/stk.git@a1ddf98466730b88a2988860a9d8000fd1833301',
-    'packaging>=21.3.0,<24.2',
 ]
 
 extra_deps = {}
@@ -61,23 +98,62 @@
     if key not in {'testing'}
 })
 
+
+cmdclass = {}
+ext_modules = []
+
+# Only install CUDA extensions if available
+if 'cu' in torch.__version__ and CUDA_HOME is not None:
+
+    cmdclass = {'build_ext': BuildExtension}
+    nvcc_flags = ['--ptxas-options=-v', '--optimize=2']
+
+    if os.environ.get('TORCH_CUDA_ARCH_LIST'):
+        # Let PyTorch builder to choose device to target for.
+        device_capability = ''
+    else:
+        device_capability_tuple = torch.cuda.get_device_capability()
+        device_capability = f'{device_capability_tuple[0]}{device_capability_tuple[1]}'
+
+    if device_capability:
+        nvcc_flags.append(
+            f'--generate-code=arch=compute_{device_capability},code=sm_{device_capability}'
+        )
+
+    ext_modules = [
+        CUDAExtension(
+            'megablocks_ops',
+            ['csrc/ops.cu'],
+            include_dirs=['csrc'],
+            extra_compile_args={
+                'cxx': ['-fopenmp'],
+                'nvcc': nvcc_flags
+            },
+        )
+    ]
+elif CUDA_HOME is None:
+    warnings.warn(
+        'Attempted to install CUDA extensions, but CUDA_HOME was None. ' +
+        'Please install CUDA and ensure that the CUDA_HOME environment ' +
+        'variable points to the installation location.')
+else:
+    warnings.warn('Warning: No CUDA devices; cuda code will not be compiled.')
+
+
 setup(
-    name="megablocks",
-    version="0.5.1",
-    author="Trevor Gale",
-    author_email="[email protected]",
-    description="MegaBlocks",
-    long_description=open('README.md').read(),
+    name=_PACKAGE_NAME,
+    version=repo_version,
+    author='Trevor Gale',
+    author_email='[email protected]',
+    description='MegaBlocks',
+    long_description=long_description,
     long_description_content_type='text/markdown',
-    url="https://github.com/stanford-futuredata/megablocks",
-    classifiers=[
-        "Programming Language :: Python :: 3",
-        "License :: OSI Approved :: BSD License",
-        "Operating System :: Unix",
-    ],
-    packages=find_packages(),
+    url='https://github.com/databricks/megablocks',
+    classifiers=classifiers,
+    packages=find_packages(exclude=['tests*', 'third_party*', 'yamls*', 'exp*', '.github*']),
     ext_modules=ext_modules,
-    cmdclass={"build_ext": BuildExtension},
+    cmdclass=cmdclass,
     install_requires=install_requires,
     extras_require=extra_deps,
+    python_requires='>=3.9',
 )