__init__.py 6.0 KB
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#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance 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, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

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import os
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import sys
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import atexit
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# The legacy core need to be removed before "import core",
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# in case of users installing paddlepaddle without -U option
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core_suffix = 'so'
if os.name == 'nt':
    core_suffix = 'pyd'

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legacy_core = (
    os.path.abspath(os.path.dirname(__file__)) + os.sep + 'core.' + core_suffix
)
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if os.path.exists(legacy_core):
    sys.stderr.write('Deleting legacy file ' + legacy_core + '\n')
    try:
        os.remove(legacy_core)
    except Exception as e:
        raise e

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# import all class inside framework into fluid module
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from . import framework
from .framework import *
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# import all class inside executor into fluid module
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from . import executor
from .executor import *
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from . import data_feed_desc
from .data_feed_desc import *

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from . import dataset
from .dataset import *

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from . import trainer_desc
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from . import io
from . import initializer
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from .initializer import set_global_initializer
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from . import layers
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from . import dygraph
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from . import backward
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from .backward import gradients
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from . import incubate
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from .param_attr import ParamAttr, WeightNormParamAttr
from .data_feeder import DataFeeder
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from .core import LoDTensor, LoDTensorArray, Scope, _Scope
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from .core import (
    CPUPlace,
    XPUPlace,
    CUDAPlace,
    CUDAPinnedPlace,
    IPUPlace,
    CustomPlace,
)
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from .lod_tensor import create_lod_tensor, create_random_int_lodtensor
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from . import unique_name
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from . import compiler
from .compiler import *
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from paddle.fluid.layers.math_op_patch import monkey_patch_variable
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from .dygraph.base import enable_dygraph, disable_dygraph
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from .dygraph.tensor_patch_methods import monkey_patch_tensor
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from .core import _cuda_synchronize
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from .trainer_desc import (
    TrainerDesc,
    DistMultiTrainer,
    PipelineTrainer,
    HeterPipelineTrainer,
    MultiTrainer,
    HeterXpuTrainer,
)
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from .backward import append_backward
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Tensor = LoDTensor
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enable_imperative = enable_dygraph
disable_imperative = disable_dygraph
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__all__ = (
    framework.__all__
    + executor.__all__
    + trainer_desc.__all__
    + lod_tensor.__all__
    + data_feed_desc.__all__
    + compiler.__all__
    + backward.__all__
    + [
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        'io',
        'initializer',
        'layers',
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        'dygraph',
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        'enable_dygraph',
        'disable_dygraph',
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        'enable_imperative',
        'disable_imperative',
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        'backward',
        'LoDTensor',
        'LoDTensorArray',
        'CPUPlace',
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        'XPUPlace',
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        'CUDAPlace',
        'CUDAPinnedPlace',
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        'IPUPlace',
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        'Tensor',
        'ParamAttr',
        'WeightNormParamAttr',
        'DataFeeder',
        'unique_name',
        'Scope',
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        '_cuda_synchronize',
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    ]
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)
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def __bootstrap__():
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    """
    Enable reading gflags from environment variables.
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    Returns:
        None
    """
    import sys
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    import os
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    import platform
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    from . import core
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    # NOTE(zhiqiu): When (1)numpy < 1.19; (2) python < 3.7,
    # unittest is always imported in numpy (maybe some versions not).
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    # so is_test is True and p2p is not inited.
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    in_test = 'unittest' in sys.modules

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    try:
        num_threads = int(os.getenv('OMP_NUM_THREADS', '1'))
    except ValueError:
        num_threads = 1

    if num_threads > 1:
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        print(
            'WARNING: OMP_NUM_THREADS set to {0}, not 1. The computation '
            'speed will not be optimized if you use data parallel. It will '
            'fail if this PaddlePaddle binary is compiled with OpenBlas since'
            ' OpenBlas does not support multi-threads.'.format(num_threads),
            file=sys.stderr,
        )
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        print('PLEASE USE OMP_NUM_THREADS WISELY.', file=sys.stderr)

    os.environ['OMP_NUM_THREADS'] = str(num_threads)
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    flag_prefix = "FLAGS_"
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    read_env_flags = [
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        key[len(flag_prefix) :]
        for key in core.globals().keys()
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        if key.startswith(flag_prefix)
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    ]
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    def remove_flag_if_exists(name):
        if name in read_env_flags:
            read_env_flags.remove(name)
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    sysstr = platform.system()
    if 'Darwin' in sysstr:
        remove_flag_if_exists('use_pinned_memory')
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    if os.name == 'nt':
        remove_flag_if_exists('cpu_deterministic')
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    if core.is_compiled_with_ipu():
        # Currently we request all ipu available for training and testing
        #   finer control of pod of IPUs will be added later
        read_env_flags += []

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    core.init_gflags(["--tryfromenv=" + ",".join(read_env_flags)])
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    # Note(zhouwei25): sys may not have argv in some cases,
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    # Such as: use Python/C API to call Python from C++
    try:
        core.init_glog(sys.argv[0])
    except Exception:
        sys.argv = [""]
        core.init_glog(sys.argv[0])
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    # don't init_p2p when in unittest to save time.
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    core.init_memory_method()
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    core.init_devices()
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    core.init_tensor_operants()
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    core.init_default_kernel_signatures()
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# TODO(panyx0718): Avoid doing complex initialization logic in __init__.py.
# Consider paddle.init(args) or paddle.main(args)
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monkey_patch_variable()
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__bootstrap__()
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monkey_patch_tensor()
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# NOTE(Aurelius84): clean up ExecutorCacheInfo in advance manually.
atexit.register(core.clear_executor_cache)
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# NOTE(Aganlengzi): clean up KernelFactory in advance manually.
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# NOTE(wangran16): clean up DeviceManager in advance manually.
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# Keep clear_kernel_factory running before clear_device_manager
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atexit.register(core.clear_device_manager)
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atexit.register(core.clear_kernel_factory)
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atexit.register(core.ProcessGroupIdMap.destroy)