import subprocess import os import os.path import errno import re import shutil import sys import fnmatch import errno import platform import glob from contextlib import contextmanager from setuptools import Command from setuptools import setup, Distribution, Extension from setuptools.command.install import install as InstallCommandBase from setuptools.command.egg_info import egg_info class BinaryDistribution(Distribution): def has_ext_modules(foo): return True RC = 0 ext_name = '.dll' if os.name == 'nt' else ('.dylib' if sys.platform == 'darwin' else '.so') def git_commit(): try: cmd = ['git', 'rev-parse', 'HEAD'] git_commit = subprocess.Popen(cmd, stdout = subprocess.PIPE, cwd="@PADDLE_SOURCE_DIR@").communicate()[0].strip() except: git_commit = 'Unknown' git_commit = git_commit.decode() return str(git_commit) def _get_version_detail(idx): assert idx < 3, "vesion info consists of %(major)d.%(minor)d.%(patch)d, \ so detail index must less than 3" if re.match('@TAG_VERSION_REGEX@', '@PADDLE_VERSION@'): version_details = '@PADDLE_VERSION@'.split('.') if len(version_details) >= 3: return version_details[idx] return 0 def get_major(): return int(_get_version_detail(0)) def get_minor(): return int(_get_version_detail(1)) def get_patch(): return str(_get_version_detail(2)) def get_cuda_version(): if '@WITH_GPU@' == 'ON': return '@CUDA_VERSION@' else: return 'False' def get_cudnn_version(): if '@WITH_GPU@' == 'ON': temp_cudnn_version = '' if '@CUDNN_MAJOR_VERSION@': temp_cudnn_version += '@CUDNN_MAJOR_VERSION@' if '@CUDNN_MINOR_VERSION@': temp_cudnn_version += '.@CUDNN_MINOR_VERSION@' if '@CUDNN_PATCHLEVEL_VERSION@': temp_cudnn_version += '.@CUDNN_PATCHLEVEL_VERSION@' return temp_cudnn_version else: return 'False' def is_taged(): try: cmd = ['git', 'describe', '--exact-match', '--tags', 'HEAD', '2>/dev/null'] git_tag = subprocess.Popen(cmd, stdout = subprocess.PIPE, cwd="@PADDLE_SOURCE_DIR@").communicate()[0].strip() git_tag = git_tag.decode() except: return False if str(git_tag).replace('v', '') == '@PADDLE_VERSION@': return True else: return False def write_version_py(filename='paddle/version/__init__.py'): cnt = '''# THIS FILE IS GENERATED FROM PADDLEPADDLE SETUP.PY # full_version = '%(major)d.%(minor)d.%(patch)s' major = '%(major)d' minor = '%(minor)d' patch = '%(patch)s' rc = '%(rc)d' cuda_version = '%(cuda)s' cudnn_version = '%(cudnn)s' istaged = %(istaged)s commit = '%(commit)s' with_mkl = '%(with_mkl)s' __all__ = ['cuda', 'cudnn', 'show'] def show(): """Get the version of paddle if `paddle` package if tagged. Otherwise, output the corresponding commit id. Returns: If paddle package is not tagged, the commit-id of paddle will be output. Otherwise, the following information will be output. full_version: version of paddle major: the major version of paddle minor: the minor version of paddle patch: the patch level version of paddle rc: whether it's rc version cuda: the cuda version of package. It will return `False` if CPU version paddle package is installed cudnn: the cudnn version of package. It will return `False` if CPU version paddle package is installed Examples: .. code-block:: python import paddle # Case 1: paddle is tagged with 2.2.0 paddle.version.show() # full_version: 2.2.0 # major: 2 # minor: 2 # patch: 0 # rc: 0 # cuda: '10.2' # cudnn: '7.6.5' # Case 2: paddle is not tagged paddle.version.show() # commit: cfa357e984bfd2ffa16820e354020529df434f7d # cuda: '10.2' # cudnn: '7.6.5' """ if istaged: print('full_version:', full_version) print('major:', major) print('minor:', minor) print('patch:', patch) print('rc:', rc) else: print('commit:', commit) print('cuda:', cuda_version) print('cudnn:', cudnn_version) def mkl(): return with_mkl def cuda(): """Get cuda version of paddle package. Returns: string: Return the version information of cuda. If paddle package is CPU version, it will return False. Examples: .. code-block:: python import paddle paddle.version.cuda() # '10.2' """ return cuda_version def cudnn(): """Get cudnn version of paddle package. Returns: string: Return the version information of cudnn. If paddle package is CPU version, it will return False. Examples: .. code-block:: python import paddle paddle.version.cudnn() # '7.6.5' """ return cudnn_version ''' commit = git_commit() dirname = os.path.dirname(filename) try: os.makedirs(dirname) except OSError as e: if e.errno != errno.EEXIST: raise with open(filename, 'w') as f: f.write(cnt % { 'major': get_major(), 'minor': get_minor(), 'patch': get_patch(), 'rc': RC, 'version': '${PADDLE_VERSION}', 'cuda': get_cuda_version(), 'cudnn': get_cudnn_version(), 'commit': commit, 'istaged': is_taged(), 'with_mkl': '@WITH_MKL@'}) write_version_py(filename='@PADDLE_BINARY_DIR@/python/paddle/version/__init__.py') def write_cuda_env_config_py(filename='paddle/cuda_env.py'): cnt = "" if '${JIT_RELEASE_WHL}' == 'ON': cnt = '''# THIS FILE IS GENERATED FROM PADDLEPADDLE SETUP.PY # import os os.environ['CUDA_CACHE_MAXSIZE'] = '805306368' ''' with open(filename, 'w') as f: f.write(cnt) write_cuda_env_config_py(filename='@PADDLE_BINARY_DIR@/python/paddle/cuda_env.py') def write_distributed_training_mode_py(filename='paddle/fluid/incubate/fleet/parameter_server/version.py'): cnt = ''' # THIS FILE IS GENERATED FROM PADDLEPADDLE SETUP.PY from paddle.fluid.incubate.fleet.base.mode import Mode BUILD_MODE=Mode.%(mode)s def is_transpiler(): return Mode.TRANSPILER == BUILD_MODE ''' dirname = os.path.dirname(filename) try: os.makedirs(dirname) except OSError as e: if e.errno != errno.EEXIST: raise with open(filename, 'w') as f: f.write(cnt % { 'mode': 'PSLIB' if '${WITH_PSLIB}' == 'ON' else 'TRANSPILER' }) write_distributed_training_mode_py(filename='@PADDLE_BINARY_DIR@/python/paddle/fluid/incubate/fleet/parameter_server/version.py') packages=['paddle', 'paddle.libs', 'paddle.utils', 'paddle.utils.gast', 'paddle.utils.cpp_extension', 'paddle.dataset', 'paddle.reader', 'paddle.distributed', 'paddle.distributed.communication', 'paddle.distributed.communication.stream', 'paddle.distributed.metric', 'paddle.distributed.ps', 'paddle.distributed.ps.utils', 'paddle.incubate', 'paddle.incubate.autograd', 'paddle.incubate.optimizer', 'paddle.incubate.checkpoint', 'paddle.incubate.operators', 'paddle.incubate.tensor', 'paddle.incubate.multiprocessing', 'paddle.incubate.nn', 'paddle.incubate.asp', 'paddle.incubate.passes', 'paddle.distribution', 'paddle.distributed.utils', 'paddle.distributed.sharding', 'paddle.distributed.fleet', 'paddle.distributed.launch', 'paddle.distributed.launch.context', 'paddle.distributed.launch.controllers', 'paddle.distributed.launch.job', 'paddle.distributed.launch.plugins', 'paddle.distributed.launch.utils', 'paddle.distributed.fleet.base', 'paddle.distributed.fleet.recompute', 'paddle.distributed.fleet.elastic', 'paddle.distributed.fleet.meta_optimizers', 'paddle.distributed.fleet.meta_optimizers.sharding', 'paddle.distributed.fleet.meta_optimizers.ascend', 'paddle.distributed.fleet.meta_optimizers.dygraph_optimizer', 'paddle.distributed.fleet.runtime', 'paddle.distributed.rpc', 'paddle.distributed.fleet.dataset', 'paddle.distributed.fleet.data_generator', 'paddle.distributed.fleet.metrics', 'paddle.distributed.fleet.proto', 'paddle.distributed.fleet.utils', 'paddle.distributed.fleet.layers', 'paddle.distributed.fleet.layers.mpu', 'paddle.distributed.fleet.meta_parallel', 'paddle.distributed.fleet.meta_parallel.pp_utils', 'paddle.distributed.fleet.meta_parallel.sharding', 'paddle.distributed.fleet.meta_parallel.parallel_layers', 'paddle.distributed.auto_parallel', 'paddle.distributed.auto_parallel.operators', 'paddle.distributed.auto_parallel.tuner', 'paddle.distributed.auto_parallel.cost', 'paddle.distributed.passes', 'paddle.distributed.models', 'paddle.distributed.models.moe', 'paddle.framework', 'paddle.jit', 'paddle.jit.dy2static', 'paddle.inference', 'paddle.inference.contrib', 'paddle.inference.contrib.utils', 'paddle.fluid', 'paddle.fluid.dygraph', 'paddle.fluid.dygraph.amp', 'paddle.fluid.proto', 'paddle.fluid.proto.profiler', 'paddle.fluid.distributed', 'paddle.fluid.layers', 'paddle.fluid.dataloader', 'paddle.fluid.contrib', 'paddle.fluid.contrib.extend_optimizer', 'paddle.fluid.contrib.mixed_precision', 'paddle.fluid.contrib.mixed_precision.bf16', 'paddle.fluid.contrib.layers', 'paddle.fluid.transpiler', 'paddle.fluid.transpiler.details', 'paddle.fluid.incubate', 'paddle.fluid.incubate.data_generator', 'paddle.fluid.incubate.fleet', 'paddle.fluid.incubate.checkpoint', 'paddle.fluid.incubate.fleet.base', 'paddle.fluid.incubate.fleet.parameter_server', 'paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler', 'paddle.fluid.incubate.fleet.parameter_server.pslib', 'paddle.fluid.incubate.fleet.parameter_server.ir', 'paddle.fluid.incubate.fleet.collective', 'paddle.fluid.incubate.fleet.utils', 'paddle.amp', 'paddle.cost_model', 'paddle.hapi', 'paddle.vision', 'paddle.vision.models', 'paddle.vision.transforms', 'paddle.vision.datasets', 'paddle.audio', 'paddle.audio.functional', 'paddle.audio.features', 'paddle.audio.datasets', 'paddle.audio.backends', 'paddle.text', 'paddle.text.datasets', 'paddle.incubate', 'paddle.incubate.nn', 'paddle.incubate.nn.functional', 'paddle.incubate.nn.layer', 'paddle.incubate.optimizer.functional', 'paddle.incubate.autograd', 'paddle.incubate.distributed', 'paddle.incubate.distributed.utils', 'paddle.incubate.distributed.utils.io', 'paddle.incubate.distributed.fleet', 'paddle.incubate.distributed.models', 'paddle.incubate.distributed.models.moe', 'paddle.incubate.distributed.models.moe.gate', 'paddle.quantization', 'paddle.quantization.quanters', 'paddle.sparse', 'paddle.sparse.nn', 'paddle.sparse.nn.layer', 'paddle.sparse.nn.functional', 'paddle.incubate.xpu', 'paddle.io', 'paddle.optimizer', 'paddle.nn', 'paddle.nn.functional', 'paddle.nn.layer', 'paddle.nn.quant', 'paddle.nn.initializer', 'paddle.nn.utils', 'paddle.metric', 'paddle.static', 'paddle.static.nn', 'paddle.static.amp', 'paddle.static.quantization', 'paddle.quantization', 'paddle.quantization.imperative', 'paddle.tensor', 'paddle.onnx', 'paddle.autograd', 'paddle.device', 'paddle.device.cuda', 'paddle.device.xpu', 'paddle.version', 'paddle.profiler', 'paddle.geometric', 'paddle.geometric.message_passing', 'paddle.geometric.sampling', ] with open('@PADDLE_SOURCE_DIR@/python/requirements.txt') as f: setup_requires = f.read().splitlines() if sys.version_info < (3,7): raise RuntimeError("Paddle only support Python version>=3.7 now") if sys.version_info >= (3,7): setup_requires_tmp = [] for setup_requires_i in setup_requires: if "<\"3.6\"" in setup_requires_i or "<=\"3.6\"" in setup_requires_i or "<\"3.5\"" in setup_requires_i or "<=\"3.5\"" in setup_requires_i or "<\"3.7\"" in setup_requires_i: continue setup_requires_tmp+=[setup_requires_i] setup_requires = setup_requires_tmp # the prefix is sys.prefix which should always be usr paddle_bins = '' if not '${WIN32}': paddle_bins = ['${PADDLE_BINARY_DIR}/paddle/scripts/paddle'] if os.name != 'nt': package_data={'paddle.fluid': ['${FLUID_CORE_NAME}' + '.so']} else: package_data={'paddle.fluid': ['${FLUID_CORE_NAME}' + '.pyd', '${FLUID_CORE_NAME}' + '.lib']} package_data['paddle.fluid'] += ['${PADDLE_BINARY_DIR}/python/paddle/cost_model/static_op_benchmark.json'] package_dir={ '': '${PADDLE_BINARY_DIR}/python', # The paddle.fluid.proto will be generated while compiling. # So that package points to other directory. 'paddle.fluid.proto.profiler': '${PADDLE_BINARY_DIR}/paddle/fluid/platform', 'paddle.fluid.proto': '${PADDLE_BINARY_DIR}/paddle/fluid/framework', 'paddle.fluid': '${PADDLE_BINARY_DIR}/python/paddle/fluid', } # put all thirdparty libraries in paddle.libs libs_path='${PADDLE_BINARY_DIR}/python/paddle/libs' package_data['paddle.libs']= [] package_data['paddle.libs']=[ ('libwarpctc' if os.name != 'nt' else 'warpctc') + ext_name, ('libwarprnnt' if os.name != 'nt' else 'warprnnt') + ext_name, ] shutil.copy('${WARPCTC_LIBRARIES}', libs_path) shutil.copy('${WARPRNNT_LIBRARIES}', libs_path) package_data['paddle.libs']+=[ os.path.basename('${LAPACK_LIB}'), os.path.basename('${BLAS_LIB}'), os.path.basename('${GFORTRAN_LIB}'), os.path.basename('${GNU_RT_LIB_1}')] shutil.copy('${BLAS_LIB}', libs_path) shutil.copy('${LAPACK_LIB}', libs_path) shutil.copy('${GFORTRAN_LIB}', libs_path) shutil.copy('${GNU_RT_LIB_1}', libs_path) if '${WITH_CUDNN_DSO}' == 'ON' and os.path.exists('${CUDNN_LIBRARY}'): package_data['paddle.libs']+=[os.path.basename('${CUDNN_LIBRARY}')] shutil.copy('${CUDNN_LIBRARY}', libs_path) if sys.platform.startswith("linux") and '${CUDNN_MAJOR_VERSION}' == '8': # libcudnn.so includes libcudnn_ops_infer.so, libcudnn_ops_train.so, # libcudnn_cnn_infer.so, libcudnn_cnn_train.so, libcudnn_adv_infer.so, # libcudnn_adv_train.so cudnn_lib_files = glob.glob(os.path.dirname('${CUDNN_LIBRARY}') + '/libcudnn_*so.8') for cudnn_lib in cudnn_lib_files: if os.path.exists(cudnn_lib): package_data['paddle.libs']+=[os.path.basename(cudnn_lib)] shutil.copy(cudnn_lib, libs_path) if not sys.platform.startswith("linux"): package_data['paddle.libs']+=[os.path.basename('${GNU_RT_LIB_2}')] shutil.copy('${GNU_RT_LIB_2}', libs_path) if '${WITH_MKL}' == 'ON': shutil.copy('${MKLML_SHARED_LIB}', libs_path) shutil.copy('${MKLML_SHARED_IOMP_LIB}', libs_path) package_data['paddle.libs']+=[('libmklml_intel' if os.name != 'nt' else 'mklml') + ext_name, ('libiomp5' if os.name != 'nt' else 'libiomp5md') + ext_name] else: if os.name == 'nt': # copy the openblas.dll shutil.copy('${OPENBLAS_SHARED_LIB}', libs_path) package_data['paddle.libs'] += ['openblas' + ext_name] elif os.name == 'posix' and platform.machine() == 'aarch64' and '${OPENBLAS_LIB}'.endswith('so'): # copy the libopenblas.so on linux+aarch64 # special: libpaddle.so without avx depends on 'libopenblas.so.0', not 'libopenblas.so' if os.path.exists('${OPENBLAS_LIB}' + '.0'): shutil.copy('${OPENBLAS_LIB}' + '.0', libs_path) package_data['paddle.libs'] += ['libopenblas.so.0'] if '${WITH_LITE}' == 'ON': shutil.copy('${LITE_SHARED_LIB}', libs_path) package_data['paddle.libs']+=['libpaddle_full_api_shared' + ext_name] if '${LITE_WITH_NNADAPTER}' == 'ON': shutil.copy('${LITE_NNADAPTER_LIB}', libs_path) package_data['paddle.libs']+=['libnnadapter' + ext_name] if '${NNADAPTER_WITH_HUAWEI_ASCEND_NPU}' == 'ON': shutil.copy('${LITE_NNADAPTER_NPU_LIB}', libs_path) package_data['paddle.libs']+=['libnnadapter_driver_huawei_ascend_npu' + ext_name] if '${WITH_CINN}' == 'ON': shutil.copy('${CINN_LIB_LOCATION}/${CINN_LIB_NAME}', libs_path) shutil.copy('${CINN_INCLUDE_DIR}/cinn/runtime/cuda/cinn_cuda_runtime_source.cuh', libs_path) package_data['paddle.libs']+=['libcinnapi.so'] package_data['paddle.libs']+=['cinn_cuda_runtime_source.cuh'] cinn_fp16_file = '${CINN_INCLUDE_DIR}/cinn/runtime/cuda/float16.h' if os.path.exists(cinn_fp16_file): shutil.copy(cinn_fp16_file, libs_path) package_data['paddle.libs']+=['float16.h'] if '${CMAKE_BUILD_TYPE}' == 'Release' and os.name != 'nt': command = "patchelf --set-rpath '$ORIGIN/' %s/${CINN_LIB_NAME}" % libs_path if os.system(command) != 0: raise Exception("patch %s/${CINN_LIB_NAME} failed, command: %s" % (libs_path, command)) if '${WITH_PSLIB}' == 'ON': shutil.copy('${PSLIB_LIB}', libs_path) if os.path.exists('${PSLIB_VERSION_PY}'): shutil.copy('${PSLIB_VERSION_PY}', '${PADDLE_BINARY_DIR}/python/paddle/fluid/incubate/fleet/parameter_server/pslib/') package_data['paddle.libs'] += ['libps' + ext_name] if '${WITH_MKLDNN}' == 'ON': if '${CMAKE_BUILD_TYPE}' == 'Release' and os.name != 'nt': # only change rpath in Release mode. # TODO(typhoonzero): use install_name_tool to patch mkl libs once # we can support mkl on mac. # # change rpath of libdnnl.so.1, add $ORIGIN/ to it. # The reason is that all thirdparty libraries in the same directory, # thus, libdnnl.so.1 will find libmklml_intel.so and libiomp5.so. command = "patchelf --set-rpath '$ORIGIN/' ${MKLDNN_SHARED_LIB}" if os.system(command) != 0: raise Exception("patch libdnnl.so failed, command: %s" % command) shutil.copy('${MKLDNN_SHARED_LIB}', libs_path) if os.name != 'nt': shutil.copy('${MKLDNN_SHARED_LIB_1}', libs_path) shutil.copy('${MKLDNN_SHARED_LIB_2}', libs_path) package_data['paddle.libs']+=['libmkldnn.so.0', 'libdnnl.so.1', 'libdnnl.so.2'] else: package_data['paddle.libs']+=['mkldnn.dll'] if '${WITH_ONNXRUNTIME}' == 'ON': shutil.copy('${ONNXRUNTIME_SHARED_LIB}', libs_path) shutil.copy('${PADDLE2ONNX_LIB}', libs_path) if os.name == 'nt': package_data['paddle.libs']+=['paddle2onnx.dll', 'onnxruntime.dll'] else: package_data['paddle.libs']+=['${PADDLE2ONNX_LIB_NAME}', '${ONNXRUNTIME_LIB_NAME}'] if '${WITH_XPU}' == 'ON': # only change rpath in Release mode, if '${CMAKE_BUILD_TYPE}' == 'Release': if os.name != 'nt': if "@APPLE@" == "1": command = "install_name_tool -id \"@loader_path/\" ${XPU_API_LIB}" else: command = "patchelf --set-rpath '$ORIGIN/' ${XPU_API_LIB}" if os.system(command) != 0: raise Exception("patch ${XPU_API_LIB} failed, command: %s" % command) shutil.copy('${XPU_API_LIB}', libs_path) package_data['paddle.libs']+=['${XPU_API_LIB_NAME}'] xpu_rt_lib_list = glob.glob('${XPU_RT_LIB}*') for xpu_rt_lib_file in xpu_rt_lib_list: shutil.copy(xpu_rt_lib_file, libs_path) package_data['paddle.libs']+=[os.path.basename(xpu_rt_lib_file)] if '${WITH_XPU_BKCL}' == 'ON': shutil.copy('${XPU_BKCL_LIB}', libs_path) package_data['paddle.libs']+=['${XPU_BKCL_LIB_NAME}'] # remove unused paddle/libs/__init__.py if os.path.isfile(libs_path+'/__init__.py'): os.remove(libs_path+'/__init__.py') package_dir['paddle.libs']=libs_path # change rpath of ${FLUID_CORE_NAME}.ext, add $ORIGIN/../libs/ to it. # The reason is that libwarpctc.ext, libiomp5.ext etc are in paddle.libs, and # ${FLUID_CORE_NAME}.ext is in paddle.fluid, thus paddle/fluid/../libs will pointer to above libraries. # This operation will fix https://github.com/PaddlePaddle/Paddle/issues/3213 if '${CMAKE_BUILD_TYPE}' == 'Release': if os.name != 'nt': # only change rpath in Release mode, since in Debug mode, ${FLUID_CORE_NAME}.xx is too large to be changed. if "@APPLE@" == "1": commands = ["install_name_tool -id '@loader_path/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/${FLUID_CORE_NAME}" + '.so'] commands.append("install_name_tool -add_rpath '@loader_path/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/${FLUID_CORE_NAME}" + '.so') else: commands = ["patchelf --set-rpath '$ORIGIN/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/${FLUID_CORE_NAME}" + '.so'] # The sw_64 not suppot patchelf, so we just disable that. if platform.machine() != 'sw_64' and platform.machine() != 'mips64': for command in commands: if os.system(command) != 0: raise Exception("patch ${FLUID_CORE_NAME}.%s failed, command: %s" % (ext_name, command)) ext_modules = [Extension('_foo', ['stub.cc'])] if os.name == 'nt': # fix the path separator under windows fix_package_dir = {} for k, v in package_dir.items(): fix_package_dir[k] = v.replace('/', '\\') package_dir = fix_package_dir ext_modules = [] elif sys.platform == 'darwin': ext_modules = [] def find_files(pattern, root, recursive=False): for dirpath, _, files in os.walk(root): for filename in fnmatch.filter(files, pattern): yield os.path.join(dirpath, filename) if not recursive: break headers = ( # paddle level api headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle')) + list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/api')) + # phi unify api header list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/api/ext')) + # custom op api list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/api/include')) + # phi api list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/common')) + # phi common headers # phi level api headers (low level api) list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi')) + # phi extension header list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/include', recursive=True)) + # phi include headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/backends', recursive=True)) + # phi backends headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/core', recursive=True)) + # phi core headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/infermeta', recursive=True)) + # phi infermeta headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/kernels')) + # phi kernels headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/kernels/sparse')) + # phi sparse kernels headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/kernels/selected_rows')) + # phi selected_rows kernels headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/kernels/strings')) + # phi sparse kernels headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/kernels/primitive')) + # phi kernel primitive api headers # capi headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/capi', recursive=True)) + # phi capi headers # profiler headers list(find_files('trace_event.h', '@PADDLE_SOURCE_DIR@/paddle/fluid/platform/profiler')) + # phi profiler headers # utils api headers list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/utils', recursive=True))) # paddle utils headers jit_layer_headers = ['layer.h', 'serializer.h', 'serializer_utils.h', 'all.h', 'function.h'] for f in jit_layer_headers: headers += list(find_files(f, '@PADDLE_SOURCE_DIR@/paddle/fluid/jit', recursive=True)) if '${WITH_MKLDNN}' == 'ON': headers += list(find_files('*', '${MKLDNN_INSTALL_DIR}/include')) # mkldnn if '${WITH_GPU}' == 'ON' or '${WITH_ROCM}' == 'ON': # externalErrorMsg.pb for External Error message headers += list(find_files('*.pb', '${externalError_INCLUDE_DIR}')) class InstallCommand(InstallCommandBase): def finalize_options(self): ret = InstallCommandBase.finalize_options(self) self.install_lib = self.install_platlib self.install_headers = os.path.join(self.install_platlib, 'paddle', 'include') return ret class InstallHeaders(Command): """Override how headers are copied. """ description = 'install C/C++ header files' user_options = [('install-dir=', 'd', 'directory to install header files to'), ('force', 'f', 'force installation (overwrite existing files)'), ] boolean_options = ['force'] def initialize_options(self): self.install_dir = None self.force = 0 self.outfiles = [] def finalize_options(self): self.set_undefined_options('install', ('install_headers', 'install_dir'), ('force', 'force')) def mkdir_and_copy_file(self, header): if 'pb.h' in header: install_dir = re.sub('${PADDLE_BINARY_DIR}/', '', header) elif 'third_party' not in header: # paddle headers install_dir = re.sub('@PADDLE_SOURCE_DIR@/', '', header) print('install_dir: ', install_dir) if 'fluid/jit' in install_dir: install_dir = re.sub('fluid/jit', 'jit', install_dir) print('fluid/jit install_dir: ', install_dir) if 'trace_event.h' in install_dir: install_dir = re.sub('fluid/platform/profiler', 'phi/backends/custom', install_dir) print('trace_event.h install_dir: ', install_dir) else: # third_party install_dir = re.sub('${THIRD_PARTY_PATH}', 'third_party', header) patterns = ['install/mkldnn/include'] for pattern in patterns: install_dir = re.sub(pattern, '', install_dir) install_dir = os.path.join(self.install_dir, os.path.dirname(install_dir)) if not os.path.exists(install_dir): self.mkpath(install_dir) return self.copy_file(header, install_dir) def run(self): hdrs = self.distribution.headers if not hdrs: return self.mkpath(self.install_dir) for header in hdrs: (out, _) = self.mkdir_and_copy_file(header) self.outfiles.append(out) def get_inputs(self): return self.distribution.headers or [] def get_outputs(self): return self.outfiles class EggInfo(egg_info): """Copy license file into `.dist-info` folder.""" def run(self): # don't duplicate license into `.dist-info` when building a distribution if not self.distribution.have_run.get('install', True): self.mkpath(self.egg_info) self.copy_file("@PADDLE_SOURCE_DIR@/LICENSE", self.egg_info) egg_info.run(self) # we redirect setuptools log for non-windows if sys.platform != 'win32': @contextmanager def redirect_stdout(): f_log = open('${SETUP_LOG_FILE}', 'w') origin_stdout = sys.stdout sys.stdout = f_log yield f_log = sys.stdout sys.stdout = origin_stdout f_log.close() else: @contextmanager def redirect_stdout(): yield # Log for PYPI with open("@PADDLE_BINARY_DIR@/python/paddle/README.md", "r", encoding='UTF-8') as f: long_description = f.read() # strip *.so to reduce package size if '${WITH_STRIP}' == 'ON': command = 'find ${PADDLE_BINARY_DIR}/python/paddle -name "*.so" | xargs -i strip {}' if os.system(command) != 0: raise Exception("strip *.so failed, command: %s" % command) with redirect_stdout(): setup(name='${PACKAGE_NAME}', version='${PADDLE_VERSION}', description='Parallel Distributed Deep Learning', long_description=long_description, long_description_content_type="text/markdown", author_email="Paddle-better@baidu.com", maintainer="PaddlePaddle", maintainer_email="Paddle-better@baidu.com", project_urls = { 'Homepage': 'https://www.paddlepaddle.org.cn/', 'Downloads': 'https://github.com/paddlepaddle/paddle' }, license='Apache Software License', packages=packages, install_requires=setup_requires, ext_modules=ext_modules, package_data=package_data, package_dir=package_dir, scripts=paddle_bins, distclass=BinaryDistribution, headers=headers, cmdclass={ 'install_headers': InstallHeaders, 'install': InstallCommand, 'egg_info': EggInfo, }, entry_points={ 'console_scripts': [ 'fleetrun = paddle.distributed.launch.main:launch' ] }, classifiers=[ 'Development Status :: 5 - Production/Stable', 'Operating System :: OS Independent', 'Intended Audience :: Developers', 'Intended Audience :: Education', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: Apache Software License', 'Programming Language :: C++', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', 'Programming Language :: Python :: 3.10', ], ) # As there are a lot of files in purelib which causes many logs, # we don't print them on the screen, and you can open `setup.py.log` # for the full logs. if os.path.exists('${SETUP_LOG_FILE}'): os.system('grep -v "purelib" ${SETUP_LOG_FILE}')