def Displayer(Cfg):
'''
This function is used to display the parameters.\n
Params:\n
- Cfg: The configurator.
'''
# Indicate whether the Cfg is a configurator or not.
assert type(Cfg) is type(Config()), 'Please input the configurator.'
# Set the displayer.
displayer = [''.ljust(20) + f'{param}:'.ljust(30) + f'{Cfg[param]}' for param in Cfg.keys()]
# Return the result of the displayer.
return "\n".join(displayer)
def Generator(paramsDir = './Params.txt'):
'''
This function is used to generate the configurator of parameters.\n
Params:\n
- paramsDir: The directory of the parameters' default setting file.
'''
# Create the configurator of parameters.
Cfg = Config()
# Get the names of parameters.
file = open(paramsDir)
lines = file.readlines()
# Initialize the parameters.
for line in lines:
Cfg[line.split("\n")[0].split(":")[0]] = Handler.Convertor(line.split("\n")[0].split(":")[1])
# Return the dictionary of the parameters.
return Cfg
def Parser(Cfg):
'''
This function is used to parse the parameters.\n
Params:\n
- Cfg: The configurator.
'''
# Indicate whether the Cfg is a configurator or not.
assert type(Cfg) is type(Config()), 'Please input the configurator.'
# Create the parameters' parser.
parser = argparse.ArgumentParser(description = 'Parameters Parser')
# Add the parameters into the parser.
for param in Cfg.keys():
parser.add_argument(f'-{param}', f'--{param}', f'-{param.lower()}', f'--{param.lower()}', f'-{param.upper()}', f'--{param.upper()}', dest = param, type = type(Cfg[param]), default = Cfg[param], help = f'The type of {param} is {type(Cfg[param])}')
# Parse the parameters.
params = vars(parser.parse_args())
# Update the configurator.
Cfg.update(params)
# Return the configurator.
return Cfg
def ArgParser():
'''
This function is used to parsing the arguments.
'''
# Getting the configurator.
CFG = Cfg
# Setting the arguments' parser.
parser = argparse.ArgumentParser(description = 'Argument Parser')
# Setting the arguments.
parser.add_argument('-lr', '--learningRate', type = float, dest = 'lr', default = CFG.lr, help = 'The learning rate should be the float and constrain in [0, 1].')
parser.add_argument('-momentum', '--momentum', type = float, dest = 'momentum', default = CFG.momentum, help = 'The momentum should be the float and constrain in [0, 1].')
parser.add_argument('-wd', '--weightDecay', type = float, dest = 'wd', default = CFG.wd, help = 'The weight decay should be the float and constrain in [0, 1].')
parser.add_argument('-smoothing', '--smoothing', type = float, dest = 'smoothing', default = CFG.smoothing, help = 'The smoothing should be the float and constrain in [0, 1]. (Other values would be seen as non-LSR)')
parser.add_argument('-channels', '--channels', type = int, dest = 'channels', default = CFG.channels, help = 'The channels should be the integer and only access three values 78, 109 and 154.')
parser.add_argument('-bs', '--batchSize', type = int, dest = 'bs', default = CFG.bs, help = 'The batch size should be the integer and larger than 1.')
parser.add_argument('-cs', '--classSize', type = int, dest = 'cs', default = CFG.cs, help = 'The class size should be the integer and larger than 1.')
parser.add_argument('-ep', '--epoches', type = int, dest = 'epoches', default = CFG.epoches, help = 'The epoches should be the integer and larger than 1.')
parser.add_argument('-seed', '--seed', type = int, dest = 'seed', default = CFG.seed, help = 'The random seed should be the integer and larger then -1.')
parser.add_argument('-gpu', '--GPUID', type = int, dest = 'GPUID', default = CFG.GPUID, help = 'The GPU ID should be the integer and larger than -1. (-1 means applying the Data Parallel training!)')
parser.add_argument('-ggm', '--graphGenerateMethod', type = str, dest = 'ggm', default = CFG.ggm, help = 'The graph generate method should be the string. (s for simple way || others for complex way)')
parser.add_argument('-gt', '--graphType', type = str, dest = 'gt', default = CFG.gt, help = 'The graph type should be the string and can only be BA, ER and WS.')
parser.add_argument('-nodes', '--nodes', type = int, dest = 'nodes', default = CFG.nodes, help = 'The nodes should be the integer and larger than 3.')
parser.add_argument('-initialNode', '--initialNode', type = int, dest = 'initialNode', default = CFG.initialNode, help = 'The initial nodes should be integer and smaller than nodes.')
parser.add_argument('-e', '-edge', type = int, dest = 'e', default = CFG.e, help = 'The edge should be the integer and larger than 0.')
parser.add_argument('-k', '--k', type = int, dest = 'k', default = CFG.k, help = 'The k should be the integer and smaller than nodes.')
parser.add_argument('-p', '--prob', type = float, dest = 'p', default = CFG.p, help = 'The prob should be the float and constrain in [0, 1].')
parser.add_argument('-graphDir', '--graphDir', type = str, dest = 'graphDir', default = CFG.graphDir, help = 'The graph dir should be the string.')
parser.add_argument('-modelDir', '--modelDir', type = str, dest = 'modelDir', default = CFG.modelDir, help = 'The model dir should be the string.')
parser.add_argument('-logDir', '--logDir', type = str, dest = 'logDir', default = CFG.logDir, help = 'The log dir should be the string.')
parser.add_argument('-dataDir', '--dataDir', type = str, dest = 'dataDir', default = CFG.dataDir, help = 'The data dir should be the string.')
# Parsing the argument.
args = vars(parser.parse_args())
# Handling the argument.
args = Configurator.Handler(args)
# Updating the configurator.
CFG.update(args)
# Returning the configurator.
return Config(CFG)
#============================================================================================# # Copyright: JarvisLee # Date: 2020/11/22 # File Name: Config.py # Description: This file is used to setting the hyperparameters and directories. #============================================================================================# # Importing the necessary library. import os import argparse from easydict import EasyDict as Config # Creating the configurator. Cfg = Config() # Setting the default values for the hyperparameters. # The default value of the class size. Cfg.cs = 3 # The default value of the learning rate. Cfg.lr = 2e-4 # The default value of the batch size. Cfg.bs = 32 # The default value of the epoches. Cfg.epoches = 100 # The default value of the random seed. Cfg.seed = 1 # The default value of the GPU ID. Cfg.GPUID = -1 # Setting the default values for the directories. # The default value of the model directory.
def argParse():
# Getting the configurator.
CFG = Cfg
# Creating the arguments' parser.
parser = argparse.ArgumentParser(description='Argument Parser')
# Setting the argument.
parser.add_argument('-vs',
'--vocabSize',
type=int,
dest='vs',
default=CFG.vs,
help='Integer => [1000, Infinite)')
parser.add_argument('-es',
'--embeddingSize',
type=int,
dest='es',
default=CFG.es,
help='Integer => [100, Infinite)')
parser.add_argument('-hs',
'--hiddenSize',
type=int,
dest='hs',
default=CFG.hs,
help='Integer => [100, Infinite)')
parser.add_argument('-cs',
'--classSize',
type=int,
dest='cs',
default=CFG.cs,
help='Integer => [1, Infinite)')
parser.add_argument('-lr',
'--learningRate',
type=float,
dest='lr',
default=CFG.lr,
help='Float => [0, 1]')
parser.add_argument('-beta1',
'--beta1',
type=float,
dest='beta1',
default=CFG.beta1,
help='Float => [0, 1]')
parser.add_argument('-beta2',
'--beta2',
type=float,
dest='beta2',
default=CFG.beta2,
help='Float => [0, 1]')
parser.add_argument('-wd',
'--weightDecay',
type=float,
dest='wd',
default=CFG.wd,
help='Float => [0, 1]')
parser.add_argument('-bs',
'--batchSize',
type=int,
dest='bs',
default=CFG.bs,
help='Integer => [1, Infinite)')
parser.add_argument('-ep',
'--epoches',
type=int,
dest='epoches',
default=CFG.epoches,
help='Integer => [1, Infinite)')
parser.add_argument('-seed',
'--seed',
type=int,
dest='seed',
default=CFG.seed,
help='Integer => [0, Infinite)')
parser.add_argument('-gpu',
'--GPUID',
type=int,
dest='GPUID',
default=CFG.GPUID,
help='Integer => [0, Infinite)')
parser.add_argument('-currentTime',
'--currentTime',
type=str,
dest='currentTime',
default=CFG.currentTime,
help='Format => Y-m-d-H-M-S')
parser.add_argument('-modelDir',
'--modelDir',
type=str,
dest='modelDir',
default=CFG.modelDir,
help='String')
parser.add_argument('-logDir',
'--logDir',
type=str,
dest='logDir',
default=CFG.logDir,
help='String')
parser.add_argument('-dataDir',
'--dataDir',
type=str,
dest='dataDir',
default=CFG.dataDir,
help='String')
# Parsing the argument.
args = vars(parser.parse_args())
# Updating the configurator.
CFG.update(args)
# Returning the configurator.
return Config(CFG)
def argParse():
# Getting the configurator.
CFG = Cfg
# Setting the arguments parser.
parser = argparse.ArgumentParser(description='Argument Parser')
# Setting the arguments.
parser.add_argument('-lrG',
'--learningRateG',
type=float,
dest='lrG',
default=CFG.lrG,
help='Float => [0, 1]')
parser.add_argument('-lrD',
'--learningRateD',
type=float,
dest='lrD',
default=CFG.lrD,
help='Float => [0, 1]')
parser.add_argument('-lt',
'--latentSize',
type=int,
dest='lt',
default=CFG.lt,
help='Integer => [1, Infinite)')
parser.add_argument('-im',
'--imageSize',
type=int,
dest='im',
default=CFG.im,
help='Integer => [1, Infinite)')
parser.add_argument('-ep',
'--epoches',
type=int,
dest='epoches',
default=CFG.epoches,
help='Integer => [1, Infinite)')
parser.add_argument('-bs',
'--batchSize',
type=int,
dest='bs',
default=CFG.bs,
help='Integer => [1, Infinite)')
parser.add_argument('-seed',
'--seed',
type=int,
dest='seed',
default=CFG.seed,
help='Integer => [0, Infinite)')
parser.add_argument('-gpu',
'--GPUID',
type=int,
dest='GPUID',
default=CFG.GPUID,
help='Integer => [0, Infinite)')
parser.add_argument('-modelDir',
'--modelDir',
type=str,
dest='modelDir',
default=CFG.modelDir,
help='String')
parser.add_argument('-logDir',
'--logDir',
type=str,
dest='logDir',
default=CFG.logDir,
help='String')
parser.add_argument('-dataDir',
'--dataDir',
type=str,
dest='dataDir',
default=CFG.dataDir,
help='String')
# Parsing the arguments.
args = vars(parser.parse_args())
args['imageSize'] = args['im'] * args['im']
# Updating the configurator.
CFG.update(args)
# Returning the configurator.
return Config(CFG)