setup.py.in 32.0 KB
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import subprocess
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import os
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import os.path
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import errno
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import re
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import shutil
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import sys
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import fnmatch
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import errno
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import platform
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import glob
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from contextlib import contextmanager
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from setuptools import Command
from setuptools import setup, Distribution, Extension
from setuptools.command.install import install as InstallCommandBase
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from setuptools.command.egg_info import egg_info
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class BinaryDistribution(Distribution):
    def has_ext_modules(foo):
        return True
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RC      = 0

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ext_name = '.dll' if os.name == 'nt' else ('.dylib' if sys.platform == 'darwin' else '.so')
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def git_commit():
    try:
        cmd = ['git', 'rev-parse', 'HEAD']
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        git_commit = subprocess.Popen(cmd, stdout = subprocess.PIPE,
            cwd="@PADDLE_SOURCE_DIR@").communicate()[0].strip()
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    except:
        git_commit = 'Unknown'
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    git_commit = git_commit.decode()
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    return str(git_commit)
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def _get_version_detail(idx):
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    assert idx < 3, "vesion info consists of %(major)d.%(minor)d.%(patch)d, \
        so detail index must less than 3"
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    if re.match('@TAG_VERSION_REGEX@', '@PADDLE_VERSION@'):
        version_details = '@PADDLE_VERSION@'.split('.')
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        if len(version_details) >= 3:
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            return version_details[idx]
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    return 0
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def get_major():
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    return int(_get_version_detail(0))
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def get_minor():
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    return int(_get_version_detail(1))
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def get_patch():
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    return str(_get_version_detail(2))
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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'

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def get_xpu_version():
    if '@WITH_XPU@' == 'ON':
        return '@XPU_BASE_DATE@'
    else:
        return 'False'

def get_xpu_xccl_version():
    if '@WITH_XPU_BKCL@' == 'ON':
        return '@XPU_XCCL_BASE_VERSION@'
    else:
        return 'False'

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def is_taged():
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    try:
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        cmd = ['git', 'describe', '--exact-match', '--tags', 'HEAD', '2>/dev/null']
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        git_tag = subprocess.Popen(cmd, stdout = subprocess.PIPE, cwd="@PADDLE_SOURCE_DIR@").communicate()[0].strip()
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        git_tag = git_tag.decode()
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    except:
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        return False

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    if str(git_tag).replace('v', '') == '@PADDLE_VERSION@':
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        return True
    else:
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        return False
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def write_version_py(filename='paddle/version/__init__.py'):
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    cnt = '''# THIS FILE IS GENERATED FROM PADDLEPADDLE SETUP.PY
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#
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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'
xpu_version      = '%(xpu)s'
xpu_xccl_version = '%(xpu_xccl)s'
istaged          = %(istaged)s
commit           = '%(commit)s'
with_mkl         = '%(with_mkl)s'

__all__ = ['cuda', 'cudnn', 'show', 'xpu', 'xpu_xccl']
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def show():
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    """Get the version of paddle if `paddle` package if tagged. Otherwise, output the corresponding commit id.
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    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
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        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
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        xpu: the xpu version of package. It will return `False` if non-XPU version paddle package is installed

        xpu_xccl: the xpu xccl version of package. It will return `False` if non-XPU version paddle package is installed

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    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'
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            # xpu: '20230114'
            # xpu_xccl: '1.0.7'
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            # Case 2: paddle is not tagged
            paddle.version.show()
            # commit: cfa357e984bfd2ffa16820e354020529df434f7d
            # cuda: '10.2'
            # cudnn: '7.6.5'
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            # xpu: '20230114'
            # xpu_xccl: '1.0.7'
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    """
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    if istaged:
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        print('full_version:', full_version)
        print('major:', major)
        print('minor:', minor)
        print('patch:', patch)
        print('rc:', rc)
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    else:
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        print('commit:', commit)
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    print('cuda:', cuda_version)
    print('cudnn:', cudnn_version)
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    print('xpu:', xpu_version)
    print('xpu_xccl:', xpu_xccl_version)
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def mkl():
    return with_mkl
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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.
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    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.
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    Examples:
        .. code-block:: python

            import paddle

            paddle.version.cudnn()
            # '7.6.5'

    """
    return cudnn_version
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def xpu():
    """Get xpu version of paddle package.

    Returns:
        string: Return the version information of xpu. If paddle package is non-XPU version, it will return False.

    Examples:
        .. code-block:: python

            import paddle

            paddle.version.xpu()
            # '20230114'

    """
    return xpu_version

def xpu_xccl():
    """Get xpu xccl version of paddle package.

    Returns:
        string: Return the version information of xpu xccl. If paddle package is non-XPU version, it will return False.

    Examples:
        .. code-block:: python

            import paddle

            paddle.version.xpu_xccl()
            # '1.0.7'

    """
    return xpu_xccl_version
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'''
    commit = git_commit()
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    dirname = os.path.dirname(filename)

    try:
        os.makedirs(dirname)
    except OSError as e:
        if e.errno != errno.EEXIST:
            raise

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    with open(filename, 'w') as f:
        f.write(cnt % {
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            'major': get_major(),
            'minor': get_minor(),
            'patch': get_patch(),
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            'rc': RC,
            'version': '${PADDLE_VERSION}',
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            'cuda': get_cuda_version(),
            'cudnn': get_cudnn_version(),
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            'xpu': get_xpu_version(),
            'xpu_xccl': get_xpu_xccl_version(),
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            'commit': commit,
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            'istaged': is_taged(),
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            'with_mkl': '@WITH_MKL@'})
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write_version_py(filename='@PADDLE_BINARY_DIR@/python/paddle/version/__init__.py')
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def write_cuda_env_config_py(filename='paddle/cuda_env.py'):
    cnt = ""
    if '${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')

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def write_distributed_training_mode_py(filename='paddle/fluid/incubate/fleet/parameter_server/version.py'):
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    cnt = '''
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# 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')
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packages=['paddle',
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          'paddle.libs',
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          'paddle.utils',
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          'paddle.utils.gast',
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          'paddle.utils.cpp_extension',
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          'paddle.dataset',
          'paddle.reader',
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          'paddle.distributed',
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          'paddle.distributed.communication',
          'paddle.distributed.communication.stream',
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          'paddle.distributed.metric',
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          'paddle.distributed.ps',
          'paddle.distributed.ps.utils',
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          'paddle.incubate',
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          'paddle.incubate.autograd',
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          'paddle.incubate.optimizer',
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          'paddle.incubate.checkpoint',
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          'paddle.incubate.operators',
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          'paddle.incubate.tensor',
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          'paddle.incubate.multiprocessing',
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          'paddle.incubate.nn',
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          'paddle.incubate.asp',
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          'paddle.incubate.passes',
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          'paddle.distribution',
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          'paddle.distributed.utils',
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          'paddle.distributed.sharding',
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          'paddle.distributed.fleet',
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          'paddle.distributed.launch',
          'paddle.distributed.launch.context',
          'paddle.distributed.launch.controllers',
          'paddle.distributed.launch.job',
          'paddle.distributed.launch.plugins',
          'paddle.distributed.launch.utils',
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          'paddle.distributed.fleet.base',
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          'paddle.distributed.fleet.recompute',
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          'paddle.distributed.fleet.elastic',
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          'paddle.distributed.fleet.meta_optimizers',
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          'paddle.distributed.fleet.meta_optimizers.sharding',
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          'paddle.distributed.fleet.meta_optimizers.ascend',
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          'paddle.distributed.fleet.meta_optimizers.dygraph_optimizer',
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          'paddle.distributed.fleet.runtime',
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          'paddle.distributed.rpc',
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          'paddle.distributed.fleet.dataset',
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          'paddle.distributed.fleet.data_generator',
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          'paddle.distributed.fleet.metrics',
          'paddle.distributed.fleet.proto',
          'paddle.distributed.fleet.utils',
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          'paddle.distributed.fleet.layers',
          'paddle.distributed.fleet.layers.mpu',
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          'paddle.distributed.fleet.meta_parallel',
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          'paddle.distributed.fleet.meta_parallel.pp_utils',
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          'paddle.distributed.fleet.meta_parallel.sharding',
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          'paddle.distributed.fleet.meta_parallel.parallel_layers',
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          'paddle.distributed.auto_parallel',
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          'paddle.distributed.auto_parallel.operators',
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          'paddle.distributed.auto_parallel.tuner',
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          'paddle.distributed.auto_parallel.cost',
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          'paddle.distributed.passes',
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          'paddle.distributed.models',
          'paddle.distributed.models.moe',
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          'paddle.framework',
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          'paddle.jit',
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          'paddle.jit.dy2static',
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          'paddle.inference',
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          'paddle.inference.contrib',
          'paddle.inference.contrib.utils',
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          'paddle.fluid',
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          'paddle.fluid.dygraph',
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          'paddle.fluid.proto',
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          'paddle.fluid.proto.profiler',
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          'paddle.fluid.layers',
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          'paddle.fluid.dataloader',
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          'paddle.fluid.contrib',
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          'paddle.fluid.contrib.extend_optimizer',
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          'paddle.fluid.contrib.layers',
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          'paddle.fluid.transpiler',
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          'paddle.fluid.transpiler.details',
          'paddle.fluid.incubate',
          'paddle.fluid.incubate.fleet',
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          'paddle.fluid.incubate.checkpoint',
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          'paddle.fluid.incubate.fleet.base',
          'paddle.fluid.incubate.fleet.parameter_server',
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          'paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler',
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          'paddle.fluid.incubate.fleet.parameter_server.ir',
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          'paddle.fluid.incubate.fleet.collective',
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          'paddle.fluid.incubate.fleet.utils',
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          'paddle.amp',
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          'paddle.cost_model',
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          'paddle.hapi',
          'paddle.vision',
          'paddle.vision.models',
          'paddle.vision.transforms',
          'paddle.vision.datasets',
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          'paddle.audio',
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	      'paddle.audio.functional',
	      'paddle.audio.features',
	      'paddle.audio.datasets',
	      'paddle.audio.backends',
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          'paddle.text',
          'paddle.text.datasets',
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          'paddle.incubate',
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          'paddle.incubate.nn',
          'paddle.incubate.nn.functional',
          'paddle.incubate.nn.layer',
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          'paddle.incubate.optimizer.functional',
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          'paddle.incubate.autograd',
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          'paddle.incubate.distributed',
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          'paddle.incubate.distributed.utils',
          'paddle.incubate.distributed.utils.io',
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          'paddle.incubate.distributed.fleet',
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          'paddle.incubate.distributed.models',
          'paddle.incubate.distributed.models.moe',
          'paddle.incubate.distributed.models.moe.gate',
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          'paddle.incubate.fleet.parameter_server.distribute_transpiler',
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          'paddle.incubate.fleet.parameter_server.pslib',
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          'paddle.quantization',
          'paddle.quantization.quanters',
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          'paddle.quantization.observers',
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          'paddle.sparse',
          'paddle.sparse.nn',
          'paddle.sparse.nn.layer',
          'paddle.sparse.nn.functional',
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          'paddle.incubate.xpu',
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          'paddle.io',
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          'paddle.optimizer',
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          'paddle.nn',
          'paddle.nn.functional',
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          'paddle.nn.layer',
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          'paddle.nn.quant',
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          'paddle.nn.quant.qat',
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          'paddle.nn.initializer',
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          'paddle.nn.utils',
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          'paddle.metric',
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          'paddle.static',
          'paddle.static.nn',
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          'paddle.static.amp',
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          'paddle.static.amp.bf16',
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          'paddle.static.quantization',
          'paddle.quantization',
          'paddle.quantization.imperative',
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          'paddle.tensor',
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          'paddle.onnx',
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          'paddle.autograd',
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          'paddle.device',
          'paddle.device.cuda',
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          'paddle.device.xpu',
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          'paddle.version',
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          'paddle.profiler',
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          'paddle.geometric',
          'paddle.geometric.message_passing',
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          'paddle.geometric.sampling',
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          ]
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with open('@PADDLE_SOURCE_DIR@/python/requirements.txt') as f:
    setup_requires = f.read().splitlines()
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if sys.version_info < (3,7):
    raise RuntimeError("Paddle only support Python version>=3.7 now")

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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

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# the prefix is sys.prefix which should always be usr
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paddle_bins = ''
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if not '${WIN32}':
    paddle_bins = ['${PADDLE_BINARY_DIR}/paddle/scripts/paddle']
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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']}

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package_data['paddle.fluid'] += ['${PADDLE_BINARY_DIR}/python/paddle/cost_model/static_op_benchmark.json']
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package_dir={
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    '': '${PADDLE_BINARY_DIR}/python',
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    # 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',
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    'paddle.fluid': '${PADDLE_BINARY_DIR}/python/paddle/fluid',
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}
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# put all thirdparty libraries in paddle.libs
libs_path='${PADDLE_BINARY_DIR}/python/paddle/libs'
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package_data['paddle.libs']= []
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package_data['paddle.libs']=[
    ('libwarpctc' if os.name != 'nt' else 'warpctc') + ext_name,
    ('libwarprnnt' if os.name != 'nt' else 'warprnnt') + ext_name,
]
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shutil.copy('${WARPCTC_LIBRARIES}', libs_path)
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shutil.copy('${WARPRNNT_LIBRARIES}', libs_path)
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package_data['paddle.libs']+=[
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    os.path.basename('${LAPACK_LIB}'),
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    os.path.basename('${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)
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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)

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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)

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if '${WITH_MKL}' == 'ON':
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    shutil.copy('${MKLML_SHARED_LIB}', libs_path)
    shutil.copy('${MKLML_SHARED_IOMP_LIB}', libs_path)
    package_data['paddle.libs']+=[('libmklml_intel' if os.name != 'nt' else 'mklml') + ext_name, ('libiomp5' if os.name != 'nt' else 'libiomp5md') + ext_name]
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else:
    if os.name == 'nt':
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        # copy the openblas.dll
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        shutil.copy('${OPENBLAS_SHARED_LIB}', libs_path)
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        package_data['paddle.libs'] += ['openblas' + ext_name]
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    elif os.name == 'posix' and platform.machine() == 'aarch64' and '${OPENBLAS_LIB}'.endswith('so'):
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        # copy the libopenblas.so on linux+aarch64
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        # special: libpaddle.so without avx depends on 'libopenblas.so.0', not 'libopenblas.so'
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        if os.path.exists('${OPENBLAS_LIB}' + '.0'):
            shutil.copy('${OPENBLAS_LIB}' + '.0', libs_path)
            package_data['paddle.libs'] += ['libopenblas.so.0']
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if '${WITH_LITE}' == 'ON':
    shutil.copy('${LITE_SHARED_LIB}', libs_path)
    package_data['paddle.libs']+=['libpaddle_full_api_shared' + ext_name]
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    if '${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('${LITE_NNADAPTER_NPU_LIB}', libs_path)
            package_data['paddle.libs']+=['libnnadapter_driver_huawei_ascend_npu' + ext_name]
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if '${WITH_CINN}' == 'ON':
    shutil.copy('${CINN_LIB_LOCATION}/${CINN_LIB_NAME}', libs_path)
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    shutil.copy('${CINN_INCLUDE_DIR}/cinn/runtime/cuda/cinn_cuda_runtime_source.cuh', libs_path)
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    package_data['paddle.libs']+=['libcinnapi.so']
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    package_data['paddle.libs']+=['cinn_cuda_runtime_source.cuh']
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    cinn_fp16_file = '${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']

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    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))
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if '${WITH_PSLIB}' == 'ON':
    shutil.copy('${PSLIB_LIB}', libs_path)
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    if os.path.exists('${PSLIB_VERSION_PY}'):
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        shutil.copy('${PSLIB_VERSION_PY}', '${PADDLE_BINARY_DIR}/python/paddle/incubate/fleet/parameter_server/pslib/')
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    package_data['paddle.libs'] += ['libps' + ext_name]

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if '${WITH_MKLDNN}' == 'ON':
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    if '${CMAKE_BUILD_TYPE}' == 'Release' and os.name != 'nt':
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        # only change rpath in Release mode.
        # TODO(typhoonzero): use install_name_tool to patch mkl libs once
        # we can support mkl on mac.
        #
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        # change rpath of libdnnl.so.1, add $ORIGIN/ to it.
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        # The reason is that all thirdparty libraries in the same directory,
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        # thus, libdnnl.so.1 will find libmklml_intel.so and libiomp5.so.
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        command = "patchelf --set-rpath '$ORIGIN/' ${MKLDNN_SHARED_LIB}"
        if os.system(command) != 0:
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            raise Exception("patch libdnnl.so failed, command: %s" % command)
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    shutil.copy('${MKLDNN_SHARED_LIB}', libs_path)
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    if os.name != 'nt':
        shutil.copy('${MKLDNN_SHARED_LIB_1}', libs_path)
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        shutil.copy('${MKLDNN_SHARED_LIB_2}', libs_path)
        package_data['paddle.libs']+=['libmkldnn.so.0', 'libdnnl.so.1', 'libdnnl.so.2']
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    else:
        package_data['paddle.libs']+=['mkldnn.dll']

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if '${WITH_ONNXRUNTIME}' == 'ON':
    shutil.copy('${ONNXRUNTIME_SHARED_LIB}', libs_path)
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    shutil.copy('${PADDLE2ONNX_LIB}', libs_path)
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    if os.name == 'nt':
        package_data['paddle.libs']+=['paddle2onnx.dll', 'onnxruntime.dll']
    else:
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        package_data['paddle.libs']+=['${PADDLE2ONNX_LIB_NAME}', '${ONNXRUNTIME_LIB_NAME}']
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if '${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)
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    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)]
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if '${WITH_XPU_BKCL}' == 'ON':
    shutil.copy('${XPU_BKCL_LIB}', libs_path)
    package_data['paddle.libs']+=['${XPU_BKCL_LIB_NAME}']

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# remove unused paddle/libs/__init__.py
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if os.path.isfile(libs_path+'/__init__.py'):
    os.remove(libs_path+'/__init__.py')
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package_dir['paddle.libs']=libs_path

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# change rpath of ${FLUID_CORE_NAME}.ext, add $ORIGIN/../libs/ to it.
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# The reason is that libwarpctc.ext, libiomp5.ext etc are in paddle.libs, and
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# ${FLUID_CORE_NAME}.ext is in paddle.fluid, thus paddle/fluid/../libs will pointer to above libraries.
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# This operation will fix https://github.com/PaddlePaddle/Paddle/issues/3213
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if '${CMAKE_BUILD_TYPE}' == 'Release':
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    if os.name != 'nt':
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        # only change rpath in Release mode, since in Debug mode, ${FLUID_CORE_NAME}.xx is too large to be changed.
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        if "@APPLE@" == "1":
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            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')
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        else:
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            commands = ["patchelf --set-rpath '$ORIGIN/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/${FLUID_CORE_NAME}" + '.so']
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        # The sw_64 not suppot patchelf, so we just disable that.
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        if platform.machine() != 'sw_64' and platform.machine() != 'mips64':
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            for command in commands:
                if os.system(command) != 0:
                    raise Exception("patch ${FLUID_CORE_NAME}.%s failed, command: %s" % (ext_name, command))
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ext_modules = [Extension('_foo', ['stub.cc'])]
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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
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    ext_modules = []
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elif sys.platform == 'darwin':
    ext_modules = []
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def find_files(pattern, root, recursive=False):
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    for dirpath, _, files in os.walk(root):
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        for filename in fnmatch.filter(files, pattern):
            yield os.path.join(dirpath, filename)
        if not recursive:
            break
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headers = (
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    # paddle level api headers
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    list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle')) +
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    list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/api')) +  # phi unify api header
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    list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/api/ext')) +  # custom op api
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    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)
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    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
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    list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/backends', recursive=True)) +  # phi backends headers
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    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
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    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
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    # capi headers
    list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/phi/capi', recursive=True)) +  # phi capi headers
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    # profiler headers
    list(find_files('trace_event.h', '@PADDLE_SOURCE_DIR@/paddle/fluid/platform/profiler')) +  # phi profiler headers
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    # utils api headers
    list(find_files('*.h', '@PADDLE_SOURCE_DIR@/paddle/utils', recursive=True))) # paddle utils headers

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jit_layer_headers = ['layer.h', 'serializer.h', 'serializer_utils.h', 'all.h', 'function.h']
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for f in jit_layer_headers:
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    headers += list(find_files(f, '@PADDLE_SOURCE_DIR@/paddle/fluid/jit', recursive=True))
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if '${WITH_MKLDNN}' == 'ON':
    headers += list(find_files('*', '${MKLDNN_INSTALL_DIR}/include')) # mkldnn

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if '${WITH_GPU}' == 'ON' or '${WITH_ROCM}' == 'ON':
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    # externalErrorMsg.pb for External Error message
    headers += list(find_files('*.pb', '${externalError_INCLUDE_DIR}'))
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class InstallCommand(InstallCommandBase):
    def finalize_options(self):
        ret = InstallCommandBase.finalize_options(self)
        self.install_lib = self.install_platlib
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        self.install_headers = os.path.join(self.install_platlib, 'paddle', 'include')
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        return ret
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class InstallHeaders(Command):
    """Override how headers are copied.
    """
    description = 'install C/C++ header files'
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    user_options = [('install-dir=', 'd',
                     'directory to install header files to'),
                    ('force', 'f',
                     'force installation (overwrite existing files)'),
                   ]
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    boolean_options = ['force']
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    def initialize_options(self):
        self.install_dir = None
        self.force = 0
        self.outfiles = []
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    def finalize_options(self):
        self.set_undefined_options('install',
                                   ('install_headers', 'install_dir'),
                                   ('force', 'force'))
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    def mkdir_and_copy_file(self, header):
        if 'pb.h' in header:
            install_dir = re.sub('${PADDLE_BINARY_DIR}/', '', header)
        elif 'third_party' not in header:
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            # paddle headers
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            install_dir = re.sub('@PADDLE_SOURCE_DIR@/', '', header)
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            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)
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            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)
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        else:
            # third_party
            install_dir = re.sub('${THIRD_PARTY_PATH}', 'third_party', header)
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            patterns = ['install/mkldnn/include']
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            for pattern in patterns:
                install_dir = re.sub(pattern, '', install_dir)
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        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)
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    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)
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    def get_inputs(self):
        return self.distribution.headers or []
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    def get_outputs(self):
        return self.outfiles

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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)

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# we redirect setuptools log for non-windows
if sys.platform != 'win32':
    @contextmanager
    def redirect_stdout():
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        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()
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else:
    @contextmanager
    def redirect_stdout():
        yield

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# Log for PYPI
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with open("@PADDLE_BINARY_DIR@/python/paddle/README.md", "r", encoding='UTF-8') as f:
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    long_description = f.read()
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# 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)

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with redirect_stdout():
    setup(name='${PACKAGE_NAME}',
        version='${PADDLE_VERSION}',
        description='Parallel Distributed Deep Learning',
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        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'
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        },
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        license='Apache Software License',
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        packages=packages,
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        install_requires=setup_requires,
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        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,
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            'egg_info': EggInfo,
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        },
        entry_points={
            'console_scripts': [
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                'fleetrun = paddle.distributed.launch.main:launch'
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            ]
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        },
        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',
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            'Programming Language :: Python :: 3.9',
            'Programming Language :: Python :: 3.10',
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        ],
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    )

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# As there are a lot of files in purelib which causes many logs,
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# we don't print them on the screen, and you can open `setup.py.log`
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# for the full logs.
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if os.path.exists('${SETUP_LOG_FILE}'):
    os.system('grep -v "purelib" ${SETUP_LOG_FILE}')