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scripts/run.py
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#!/usr/bin/env python # -*- coding: utf-8 -*- # Authors: Titouan Parcollet # Imports. import sys; sys.path += [".", ".."] import argparse as Ap import logging as L import numpy as np import os, pdb, sys import time import tensorflow as tf from keras.backend.tensorflow_backend import set_session __version__ = "1.0.0" # # Message Formatter # class MsgFormatter(L.Formatter): """Message Formatter Formats messages with time format YYYY-MM-DD HH:MM:SS.mmm TZ """ def formatTime(self, record, datefmt): t = record.created timeFrac = abs(t-long(t)) timeStruct = time.localtime(record.created) timeString = "" timeString += time.strftime("%F %T", timeStruct) timeString += "{:.3f} ".format(timeFrac)[1:] timeString += time.strftime("%Z", timeStruct) return timeString ############################################################################################################# ############################## Subcommands ################################## ############################################################################################################# class Subcommand(object): name = None @classmethod def addArgParser(cls, subp, *args, **kwargs): argp = subp.add_parser(cls.name, usage=cls.__doc__, *args, **kwargs) cls.addArgs(argp) argp.set_defaults(__subcmdfn__=cls.run) return argp @classmethod def addArgs(cls, argp): pass @classmethod def run(cls, d): pass class Screw(Subcommand): """Screw around with me in Screw(Subcommand).""" name = "screw" @classmethod def run(cls, d): print(cls.__doc__) class Train(Subcommand): name = "train" LOGLEVELS = {"none":L.NOTSET, "debug": L.DEBUG, "info": L.INFO, "warn":L.WARN, "err": L.ERROR, "crit": L.CRITICAL} @classmethod def addArgs(cls, argp): argp.add_argument("-d", "--datadir", default=".", type=str, help="Path to datasets directory.") argp.add_argument("-w", "--workdir", default=".", type=str, help="Path to the workspace directory for this experiment.") argp.add_argument("-l", "--loglevel", default="info", type=str, choices=cls.LOGLEVELS.keys(), help="Logging severity level.") argp.add_argument("-s", "--seed", default=0xe4223644e98b8e64, type=long, help="Seed for PRNGs.") argp.add_argument("--summary", action="store_true", help="""Print a summary of the network.""") argp.add_argument("--model", default="real", type=str, choices=["quaternion", "real"], help="Dataset Selection.") argp.add_argument("--dropout", default=0, type=float, help="Dropout probability.") argp.add_argument("-n", "--num-epochs", default=1000, type=int, help="Number of epochs") argp.add_argument("--start-filter", "--sf", default=11, type=int, help="Number of feature maps in starting stage") argp.add_argument("--num-layers", "--nl", default=10, type=int, help="Number of layers") argp.add_argument("--act", default="relu", type=str, choices=["relu","sigmoid","tanh"], help="Activation.") argp.add_argument("--aact", default="none", type=str, choices=["none","prelu"], help="Advanced Activation.") argp.add_argument("--quat-init", default='quaternion', type=str, help="Initializer for the quaternion kernel.") optp = argp.add_argument_group("Optimizers", "Tunables for all optimizers") optp.add_argument("--optimizer", "--opt", default="nag", type=str, choices=["sgd", "nag", "adam", "rmsprop"], help="Optimizer selection.") optp.add_argument("--clipnorm", "--cn", default=1.0, type=float, help="The norm of the gradient will be clipped at this magnitude.") optp.add_argument("--clipval", "--cv", default=1.0, type=float, help="The values of the gradients will be individually clipped at this magnitude.") optp.add_argument("--l2", default=0, type=float, help="L2 penalty.") optp.add_argument("--lr", default=1e-4, type=float, help="Master learning rate for optimizers.") optp.add_argument("--momentum", "--mom", default=0.9, type=float, help="Momentum for optimizers supporting momentum.") optp.add_argument("--decay", default=0, type=float, help="Learning rate decay for optimizers.") optp = argp.add_argument_group("Adam", "Tunables for Adam optimizer") optp.add_argument("--beta1", default=0.9, type=float, help="Beta1 for Adam.") optp.add_argument("--beta2", default=0.999, type=float, help="Beta2 for Adam.") optp.add_argument("--device", default="0", type=str, help="CUDA Device, starting at 0.") optp.add_argument("--gpus", default=1, type=int, help="Number of GPUs to be used, starting at 1") optp.add_argument("--memory", default=1.0, type=float, help="Memory to be allocated on the selected device, only for tensorflow backend, from 0 to 1") optp.add_argument("--save-prefix", default="", type=str, help="Save prefix for resuming and saving best model") @classmethod def run(cls, d): if not os.path.isdir(d.workdir): os.mkdir(d.workdir) logDir = os.path.join(d.workdir, "logs") if not os.path.isdir(logDir): os.mkdir(logDir) logFormatter = MsgFormatter ("[%(asctime)s ~~ %(levelname)-8s] %(message)s") stdoutLogSHandler = L.StreamHandler(sys.stdout) stdoutLogSHandler .setLevel (cls.LOGLEVELS[d.loglevel]) stdoutLogSHandler .setFormatter (logFormatter) defltLogger = L.getLogger () defltLogger .setLevel (cls.LOGLEVELS[d.loglevel]) defltLogger .addHandler (stdoutLogSHandler) trainLogFilename = os.path.join(d.workdir, "logs", "train.txt") trainLogFHandler = L.FileHandler (trainLogFilename, "a", "UTF-8", delay=True) trainLogFHandler .setLevel (cls.LOGLEVELS[d.loglevel]) trainLogFHandler .setFormatter (logFormatter) trainLogger = L.getLogger ("train") trainLogger .setLevel (cls.LOGLEVELS[d.loglevel]) trainLogger .addHandler (trainLogFHandler) entryLogFilename = os.path.join(d.workdir, "logs", "entry.txt") entryLogFHandler = L.FileHandler (entryLogFilename, "a", "UTF-8", delay=True) entryLogFHandler .setLevel (cls.LOGLEVELS[d.loglevel]) entryLogFHandler .setFormatter (logFormatter) entryLogger = L.getLogger ("entry") entryLogger .setLevel (cls.LOGLEVELS[d.loglevel]) entryLogger .addHandler (entryLogFHandler) np.random.seed(d.seed % 2**32) import training;training.train(d) ############################################################################################################# ############################## Argument Parsers ################################# ############################################################################################################# def getArgParser(prog): argp = Ap.ArgumentParser(prog = prog, usage = None, description = None, epilog = None, version = __version__) subp = argp.add_subparsers() argp.set_defaults(argp=argp) argp.set_defaults(subp=subp) # Add global args to argp here? # ... # Add subcommands for v in globals().itervalues(): if(isinstance(v, type) and issubclass(v, Subcommand) and v != Subcommand): v.addArgParser(subp) # Return argument parser. return argp ############################################################################################################# ############################## Main ################################## ############################################################################################################# def main(argv): sys.setrecursionlimit(10000) d = getArgParser(argv[0]).parse_args(argv[1:]) return d.__subcmdfn__(d) if __name__ == "__main__": main(sys.argv) |