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139 lines
4.2 KiB
139 lines
4.2 KiB
# 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");
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# you may not use this file except in compliance with the License.
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# 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
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# 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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import framework
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from framework import *
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# import all class inside executor into fluid module
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import executor
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from executor import *
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import trainer
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from trainer import Trainer
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from trainer import BeginEpochEvent
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from trainer import EndEpochEvent
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from trainer import BeginStepEvent
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from trainer import EndStepEvent
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from trainer import CheckpointConfig
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import inferencer
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from inferencer import Inferencer
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import io
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import evaluator
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import initializer
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import layers
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import nets
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import optimizer
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import backward
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import regularizer
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import average
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import metrics
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import transpiler
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from param_attr import ParamAttr, WeightNormParamAttr
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from data_feeder import DataFeeder
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from core import LoDTensor, CPUPlace, CUDAPlace, CUDAPinnedPlace, Scope
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from transpiler import DistributeTranspiler, InferenceTranspiler, \
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memory_optimize, release_memory
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from concurrency import (Go, make_channel, channel_send, channel_recv,
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channel_close, Select)
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from lod_tensor import create_lod_tensor, create_random_int_lodtensor
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import clip
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import profiler
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import unique_name
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import recordio_writer
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import parallel_executor
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from parallel_executor import *
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Tensor = LoDTensor
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__all__ = framework.__all__ + executor.__all__ + concurrency.__all__ + \
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trainer.__all__ + inferencer.__all__ + transpiler.__all__ + \
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parallel_executor.__all__ + lod_tensor.__all__ + [
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'io',
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'initializer',
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'layers',
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'transpiler'
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'nets',
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'optimizer',
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'learning_rate_decay',
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'backward',
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'regularizer',
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'LoDTensor',
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'CPUPlace',
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'CUDAPlace',
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'CUDAPinnedPlace',
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'Tensor',
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'ParamAttr',
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'WeightNormParamAttr',
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'DataFeeder',
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'clip',
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'profiler',
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'unique_name',
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'recordio_writer',
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'Scope',
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]
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def __bootstrap__():
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"""
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Enable reading gflags from environment variables.
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Returns:
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None
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"""
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import sys
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import core
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import os
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in_test = 'unittest' in sys.modules
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try:
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num_threads = int(os.getenv('OMP_NUM_THREADS', '1'))
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except ValueError:
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num_threads = 1
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if num_threads > 1:
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print(
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'WARNING: OMP_NUM_THREADS set to {0}, not 1. The computation '
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'speed will not be optimized if you use data parallel. It will '
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'fail if this PaddlePaddle binary is compiled with OpenBlas since'
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' OpenBlas does not support multi-threads.'.format(num_threads),
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file=sys.stderr)
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print('PLEASE USE OMP_NUM_THREADS WISELY.', file=sys.stderr)
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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'
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]
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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]] +
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["--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.
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core.init_devices(not in_test)
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# TODO(panyx0718): Avoid doing complex initialization logic in __init__.py.
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# Consider paddle.init(args) or paddle.main(args)
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layers.monkey_patch_variable()
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__bootstrap__()
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