__init__.py 4.5 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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from __future__ import print_function
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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 trainer
from .trainer import Trainer
from .trainer import BeginEpochEvent
from .trainer import EndEpochEvent
from .trainer import BeginStepEvent
from .trainer import EndStepEvent
from .trainer import CheckpointConfig
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from . import inferencer
from .inferencer import Inferencer
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from . import io
from . import evaluator
from . import initializer
from . import layers
from . import contrib
from . import nets
from . import optimizer
from . import backward
from . import regularizer
from . import average
from . import metrics
from . import transpiler
from .param_attr import ParamAttr, WeightNormParamAttr
from .data_feeder import DataFeeder
from .core import LoDTensor, LoDTensorArray, CPUPlace, CUDAPlace, CUDAPinnedPlace, Scope
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from .transpiler import DistributeTranspiler, \
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    memory_optimize, release_memory, DistributeTranspilerConfig
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from .lod_tensor import create_lod_tensor, create_random_int_lodtensor
from . import clip
from . import profiler
from . import unique_name
from . import recordio_writer
from . import parallel_executor
from .parallel_executor import *
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from paddle.fluid.layers.math_op_patch import monkey_patch_variable
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Tensor = LoDTensor
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__all__ = framework.__all__ + executor.__all__ + \
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    trainer.__all__ + inferencer.__all__ + transpiler.__all__ + \
    parallel_executor.__all__ + lod_tensor.__all__ + [
        'io',
        'initializer',
        'layers',
        'contrib',
        'transpiler',
        'nets',
        'optimizer',
        'learning_rate_decay',
        'backward',
        'regularizer',
        'LoDTensor',
        'LoDTensorArray',
        'CPUPlace',
        'CUDAPlace',
        'CUDAPinnedPlace',
        'Tensor',
        'ParamAttr',
        'WeightNormParamAttr',
        'DataFeeder',
        'clip',
        'profiler',
        'unique_name',
        'recordio_writer',
        'Scope',
    ]
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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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    from . import core
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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:
        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)
        print('PLEASE USE OMP_NUM_THREADS WISELY.', file=sys.stderr)

    os.environ['OMP_NUM_THREADS'] = str(num_threads)

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    read_env_flags = [
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        'use_pinned_memory', 'check_nan_inf', 'benchmark', 'warpctc_dir',
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        'eager_delete_scope', 'use_mkldnn', 'initial_cpu_memory_in_mb',
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        'init_allocated_mem', 'free_idle_memory', 'paddle_num_threads',
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        "dist_threadpool_size", 'cpu_deterministic', 'eager_delete_tensor_gb'
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    ]
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    if core.is_compiled_with_dist():
        read_env_flags.append('rpc_deadline')
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        read_env_flags.append('rpc_server_profile_period')
        read_env_flags.append('rpc_server_profile_path')
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    if core.is_compiled_with_cuda():
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        read_env_flags += [
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            'fraction_of_gpu_memory_to_use', 'cudnn_deterministic'
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        ]
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    core.init_gflags([sys.argv[0]] +
                     ["--tryfromenv=" + ",".join(read_env_flags)])
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    core.init_glog(sys.argv[0])
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    # don't init_p2p when in unittest to save time.
    core.init_devices(not in_test)
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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__()