# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # 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 # # http://www.apache.org/licenses/LICENSE-2.0 # # 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. from __future__ import print_function # import all class inside framework into fluid module import framework from framework import * # import all class inside executor into fluid module import executor from executor import * 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 import inferencer from inferencer import Inferencer import io import evaluator import initializer import layers import nets import optimizer import backward import regularizer import average import metrics import transpiler from param_attr import ParamAttr, WeightNormParamAttr from data_feeder import DataFeeder from core import LoDTensor, CPUPlace, CUDAPlace, CUDAPinnedPlace, Scope from transpiler import DistributeTranspiler, InferenceTranspiler, \ memory_optimize, release_memory from concurrency import (Go, make_channel, channel_send, channel_recv, channel_close, Select) from lod_tensor import create_lod_tensor, create_random_int_lodtensor import clip import profiler import unique_name import recordio_writer import parallel_executor from parallel_executor import * Tensor = LoDTensor __all__ = framework.__all__ + executor.__all__ + concurrency.__all__ + \ trainer.__all__ + inferencer.__all__ + transpiler.__all__ + \ parallel_executor.__all__ + lod_tensor.__all__ + [ 'io', 'initializer', 'layers', 'transpiler' 'nets', 'optimizer', 'learning_rate_decay', 'backward', 'regularizer', 'LoDTensor', 'CPUPlace', 'CUDAPlace', 'CUDAPinnedPlace', 'Tensor', 'ParamAttr', 'WeightNormParamAttr', 'DataFeeder', 'clip', 'profiler', 'unique_name', 'recordio_writer', 'Scope', ] def __bootstrap__(): """ Enable reading gflags from environment variables. Returns: None """ import sys import core import os in_test = 'unittest' in sys.modules 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) read_env_flags = [ 'use_pinned_memory', 'check_nan_inf', 'benchmark', 'warpctc_dir', 'eager_delete_scope', 'use_mkldnn', 'initial_cpu_memory_in_mb', 'init_allocated_mem', 'rpc_deadline' ] if core.is_compiled_with_cuda(): read_env_flags += [ 'fraction_of_gpu_memory_to_use', 'cudnn_deterministic' ] core.init_gflags([sys.argv[0]] + ["--tryfromenv=" + ",".join(read_env_flags)]) core.init_glog(sys.argv[0]) # don't init_p2p when in unittest to save time. core.init_devices(not in_test) # TODO(panyx0718): Avoid doing complex initialization logic in __init__.py. # Consider paddle.init(args) or paddle.main(args) layers.monkey_patch_variable() __bootstrap__()