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 io import evaluator import initializer import layers import nets import optimizer import backward import regularizer from param_attr import ParamAttr from data_feeder import DataFeeder from core import LoDTensor, CPUPlace, CUDAPlace from distribute_transpiler import DistributeTranspiler from distribute_transpiler_simple import SimpleDistributeTranspiler import clip from memory_optimization_transpiler import memory_optimize Tensor = LoDTensor __all__ = framework.__all__ + executor.__all__ + [ 'io', 'initializer', 'layers', 'nets', 'optimizer', 'backward', 'regularizer', 'LoDTensor', 'CPUPlace', 'CUDAPlace', 'Tensor', 'ParamAttr', 'DataFeeder', 'clip', 'SimpleDistributeTranspiler', 'DistributeTranspiler', 'memory_optimize' ] def __bootstrap__(): """ Enable reading gflags from environment variables. Returns: None """ import sys import core import os 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'] if core.is_compile_gpu(): read_env_flags += ['fraction_of_gpu_memory_to_use', 'op_sync'] core.init_gflags([sys.argv[0]] + ["--tryfromenv=" + ",".join(read_env_flags)]) core.init_glog(sys.argv[0]) core.init_devices() __bootstrap__()