55bd786fe2
* [REFACTOR][RUNTIME] Move NDArray to Object System. Previously NDArray has its own object reference counting mechanism. This PR migrates NDArray to the unified object protocol. The calling convention of NDArray remained intact. That means NDArray still has its own type_code and its handle is still DLTensor compatible. In order to do so, this PR added a few minimum runtime type detection in TVMArgValue and RetValue only when the corresponding type is a base type(ObjectRef) that could also refer to NDArray. This means that even if we return a base reference object ObjectRef which refers to the NDArray. The type_code will still be translated correctly as kNDArrayContainer. If we assign a non-base type(say Expr) that we know is not compatible with NDArray during compile time, no runtime type detection will be performed. This PR also adopts the object protocol for NDArray sub-classing and removed the legacy NDArray subclass protocol. Examples in apps/extension are now updated to reflect that. Making NDArray as an Object brings all the benefits of the object system. For example, we can now use the Array container to store NDArrays. * Address review comments
187 lines
5.9 KiB
Python
187 lines
5.9 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# pylint: disable=invalid-name, exec-used
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"""Setup TVM package."""
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from __future__ import absolute_import
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import os
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import shutil
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import sys
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import sysconfig
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import platform
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from setuptools import find_packages
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from setuptools.dist import Distribution
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# need to use distutils.core for correct placement of cython dll
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if "--inplace" in sys.argv:
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from distutils.core import setup
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from distutils.extension import Extension
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else:
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from setuptools import setup
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from setuptools.extension import Extension
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CURRENT_DIR = os.path.dirname(__file__)
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def get_lib_path():
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"""Get library path, name and version"""
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# We can not import `libinfo.py` in setup.py directly since __init__.py
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# Will be invoked which introduces dependences
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libinfo_py = os.path.join(CURRENT_DIR, './tvm/_ffi/libinfo.py')
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libinfo = {'__file__': libinfo_py}
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exec(compile(open(libinfo_py, "rb").read(), libinfo_py, 'exec'), libinfo, libinfo)
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version = libinfo['__version__']
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if not os.getenv('CONDA_BUILD'):
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lib_path = libinfo['find_lib_path']()
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libs = [lib_path[0]]
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if libs[0].find("runtime") == -1:
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for name in lib_path[1:]:
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if name.find("runtime") != -1:
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libs.append(name)
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break
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else:
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libs = None
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return libs, version
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LIB_LIST, __version__ = get_lib_path()
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def config_cython():
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"""Try to configure cython and return cython configuration"""
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if os.name == 'nt':
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print("WARNING: Cython is not supported on Windows, will compile without cython module")
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return []
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sys_cflags = sysconfig.get_config_var("CFLAGS")
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if "i386" in sys_cflags and "x86_64" in sys_cflags:
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print("WARNING: Cython library may not be compiled correctly with both i386 and x64")
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return []
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try:
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from Cython.Build import cythonize
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# from setuptools.extension import Extension
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if sys.version_info >= (3, 0):
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subdir = "_cy3"
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else:
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subdir = "_cy2"
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ret = []
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path = "tvm/_ffi/_cython"
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if os.name == 'nt':
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library_dirs = ['tvm', '../build/Release', '../build']
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libraries = ['libtvm']
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else:
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library_dirs = None
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libraries = None
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for fn in os.listdir(path):
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if not fn.endswith(".pyx"):
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continue
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ret.append(Extension(
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"tvm._ffi.%s.%s" % (subdir, fn[:-4]),
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["tvm/_ffi/_cython/%s" % fn],
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include_dirs=["../include/",
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"../3rdparty/dmlc-core/include",
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"../3rdparty/dlpack/include",
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],
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extra_compile_args=["-std=c++11"],
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library_dirs=library_dirs,
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libraries=libraries,
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language="c++"))
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return cythonize(ret, compiler_directives={"language_level": 3})
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except ImportError:
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print("WARNING: Cython is not installed, will compile without cython module")
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return []
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class BinaryDistribution(Distribution):
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def has_ext_modules(self):
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return True
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def is_pure(self):
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return False
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include_libs = False
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wheel_include_libs = False
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if not os.getenv('CONDA_BUILD'):
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if "bdist_wheel" in sys.argv:
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wheel_include_libs = True
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else:
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include_libs = True
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setup_kwargs = {}
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# For bdist_wheel only
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if wheel_include_libs:
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with open("MANIFEST.in", "w") as fo:
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for path in LIB_LIST:
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shutil.copy(path, os.path.join(CURRENT_DIR, 'tvm'))
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_, libname = os.path.split(path)
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fo.write("include tvm/%s\n" % libname)
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setup_kwargs = {
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"include_package_data": True
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}
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if include_libs:
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curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
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for i, path in enumerate(LIB_LIST):
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LIB_LIST[i] = os.path.relpath(path, curr_path)
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setup_kwargs = {
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"include_package_data": True,
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"data_files": [('tvm', LIB_LIST)]
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}
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def get_package_data_files():
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# Relay standard libraries
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return ['relay/std/prelude.rly']
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setup(name='tvm',
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version=__version__,
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description="TVM: An End to End Tensor IR/DSL Stack for Deep Learning Systems",
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zip_safe=False,
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install_requires=[
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'numpy',
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'decorator',
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'attrs',
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'psutil',
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],
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extras_require={'test': ['pillow',
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'matplotlib'],
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'extra_feature': ['tornado',
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'psutil',
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'xgboost',
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'mypy',
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'orderedset',
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'antlr4-python3-runtime']},
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packages=find_packages(),
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package_dir={'tvm': 'tvm'},
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package_data={'tvm': get_package_data_files()},
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distclass=BinaryDistribution,
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url='https://github.com/apache/incubator-tvm',
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ext_modules=config_cython(),
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**setup_kwargs)
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if wheel_include_libs:
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# Wheel cleanup
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os.remove("MANIFEST.in")
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for path in LIB_LIST:
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_, libname = os.path.split(path)
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os.remove("tvm/%s" % libname)
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