()
return args
parser.add_argument('-lr_warmup', type=float, default=0.002)
  parser.add_argument('-lr_schedule', type=str, default='warmup_linear')
  parser.add_argument("-lr",default=6.25e-5,type=float)
  parser.add_argument("-sgdlr",default=0.1,type=float)
  parser.add_argument('-b1', type=float, default=0.9)
  parser.add_argument('-b2', type=float, default=0.999)
  parser.add_argument('-e', type=float, default=1e-8)
  parser.add_argument('-l2', type=float, default=0.01)
  parser.add_argument('-vector_l2', action='store_true')
parser.add_argument('-lr_warmup', type=float, default=0.002)
  parser.add_argument('-lr_schedule', type=str, default='warmup_linear')
  parser.add_argument("-lr",default=6.25e-5,type=float)
  parser.add_argument("-sgdlr",default=0.1,type=float)
  parser.add_argument('-b1', type=float, default=0.9)
  parser.add_argument('-b2', type=float, default=0.999)
  parser.add_argument('-e', type=float, default=1e-8)
  parser.add_argument('-l2', type=float, default=0.01)
  parser.add_argument('-vector_l2', action='store_true')
parser . add_argument ( - lr_warmup type = float default = 0 . 002 ) parser . add_argument ( - lr_schedule type = str default = warmup_linear ) parser . add_argument ( - lr default = 6 . 25e - 5 type = float ) parser . add_argument ( - sgdlr default = 0 . 1 type = float ) parser . add_argument ( - b1 type = float default = 0 . 9 ) parser . add_argument ( - b2 type = float default = 0 . 999 ) parser . add_argument ( - e type = float default = 1e - 8 ) parser . add_argument ( - l2 type = float default = 0 . 01 ) parser . add_argument ( - vector_l2 action = store_true )
def pargs():
  parser = argparse.ArgumentParser(description='Graph Doc Plan')

  #model
  parser.add_argument("-model",default="graph",help="model types: 'graph' for graph transformer (default), 'gat' for graph attention network, 'ents' for entity-only model." )
  parser.add_argument("-esz",default=500,type=int,help='embedding size')
  parser.add_argument("-hsz",default=500,type=int,help="hidden state size")
  parser.add_argument("-prop",default=6,type=int,help="number of layers/blocks")
  parser.add_argument("-title",action='store_true',help="use title as additional input")
  parser.add_argument("-drop",default=0.1,type=float,help="dropout rate")
  parser.add_argument("-embdrop",default=0,type=float,help="embedding dropout")
  parser.add_argument("-layers",default=2,type=int,help='encoder lstm layers')
  #parser.add_argument("-blockdrop",default=0.1)
  #parser.add_argument("-gdrop",default=0.3,type=float)
  #parser.add_argument("-attnheads",default=3,type=int,
  #parser.add_argument("-elmoVocab",default="../data/elmoVocab.txt",type=str)
  #parser.add_argument("-elmo",action='store_true')
  #parser.add_argument("-heads",default=4,type=int)



  # training and loss
  parser.add_argument("-cl",default=None,type=float,help="Coverage loss")
  parser.add_argument("-bsz",default=32,type=int)
  parser.add_argument("-epochs",default=20,type=int)
  parser.add_argument("-clip",default=1,type=float,help='clip grads')
  parser.add_argument("-t1size",default=32,type=int,help="batch size for short targets")
  parser.add_argument("-t2size",default=16,type=int,help="batch size for medium length targets")
  parser.add_argument("-t3size",default=8,type=int,help="batch size for long targets")

  #optim
  '''
  parser.add_argument('-lr_warmup', type=float, default=0.002)
  parser.add_argument('-lr_schedule', type=str, default='warmup_linear')
  parser.add_argument("-lr",default=6.25e-5,type=float)
  parser.add_argument("-sgdlr",default=0.1,type=float)
  parser.add_argument('-b1', type=float, default=0.9)
  parser.add_argument('-b2', type=float, default=0.999)
  parser.add_argument('-e', type=float, default=1e-8)
  parser.add_argument('-l2', type=float, default=0.01)
  parser.add_argument('-vector_l2', action='store_true')
  '''
  parser.add_argument("-lr",default=0.1,type=float,help='learning rate')
  parser.add_argument("-lrhigh",default=0.5,type=float,help="high learning rate for cycling")
  parser.add_argument("-lrstep",default=4, type=int,help='steps in cycle')
  parser.add_argument("-lrwarm",action="store_true",help='use cycling learning rate')
  parser.add_argument("-lrdecay",action="store_true",help="use learning rate decay")


  #parser.add_argument('-max_grad_norm', type=int, default=1)

  #data
  parser.add_argument("-nosave",action='store_false',help='dont save')
  parser.add_argument("-save",required=True,help="where to save model")
  parser.add_argument("-outunk",default=5,type=int,help="unk @ for targets")
  parser.add_argument("-entunk",default=5,type=int,help="unk @ for entity vocabulary")
  parser.add_argument("-datadir",default="data/")
  parser.add_argument("-data",default="preprocessed.train.tsv",help="preprocessed data")
  parser.add_argument("-traindata",default="preprocessed.train.tsv",help="preprocessed train data")
  parser.add_argument("-relvocab",default="relations.vocab",type=str,help='vocabulary of graph relations')
  parser.add_argument("-savevocab",default=None,type=str)
  parser.add_argument("-loadvocab",default=None,type=str)

  #eval
  parser.add_argument("-eval",action='store_true')


  #inference
  parser.add_argument("-max",default=200,type=int,help="max length of generation")
  parser.add_argument("-test",action='store_true')
  #parser.add_argument("-sample",action='store_true')
  parser.add_argument("-inputs",default="../data/fullGraph.test.tsv",type=str)


  parser.add_argument("-sparse",action='store_true',help="sparse graphs (NOT CURRENTLY IMPLEMENTED)")
  parser.add_argument("-plan",action='store_true',help="plan and write (NOT IMPLEMENTED)")
  parser.add_argument("-ckpt",default=None,type=str,help='load checkpoint')
  parser.add_argument("-plweight",default=0.2,type=float,help="plan weight (NOT IMPLEMENTED)")
  parser.add_argument("-entdetach",action='store_true',help='dont backprop into entity embeddings')

  parser.add_argument("-gpu",default=0,type=int)
  args = parser.parse_args()
  if args.gpu == -1:
    args.gpu = 'cpu'
  args.device = torch.device(args.gpu)

  #args.options_file = "../elmo/elmo_2x2048_256_2048cnn_1xhighway_options.json"
  #args.weight_file = "../elmo/elmo_2x2048_256_2048cnn_1xhighway_weights.hdf5"

  return args
def pargs ( ) : parser = argparse . ArgumentParser ( description = 'Graph Doc Plan' ) #model parser . add_argument ( "-model" , default = "graph" , help = "model types: 'graph' for graph transformer (default), 'gat' for graph attention network, 'ents' for entity-only model." ) parser . add_argument ( "-esz" , default = 500 , type = int , help = 'embedding size' ) parser . add_argument ( "-hsz" , default = 500 , type = int , help = "hidden state size" ) parser . add_argument ( "-prop" , default = 6 , type = int , help = "number of layers/blocks" ) parser . add_argument ( "-title" , action = 'store_true' , help = "use title as additional input" ) parser . add_argument ( "-drop" , default = 0.1 , type = float , help = "dropout rate" ) parser . add_argument ( "-embdrop" , default = 0 , type = float , help = "embedding dropout" ) parser . add_argument ( "-layers" , default = 2 , type = int , help = 'encoder lstm layers' ) #parser.add_argument("-blockdrop",default=0.1) #parser.add_argument("-gdrop",default=0.3,type=float) #parser.add_argument("-attnheads",default=3,type=int, #parser.add_argument("-elmoVocab",default="../data/elmoVocab.txt",type=str) #parser.add_argument("-elmo",action='store_true') #parser.add_argument("-heads",default=4,type=int) # training and loss parser . add_argument ( "-cl" , default = None , type = float , help = "Coverage loss" ) parser . add_argument ( "-bsz" , default = 32 , type = int ) parser . add_argument ( "-epochs" , default = 20 , type = int ) parser . add_argument ( "-clip" , default = 1 , type = float , help = 'clip grads' ) parser . add_argument ( "-t1size" , default = 32 , type = int , help = "batch size for short targets" ) parser . add_argument ( "-t2size" , default = 16 , type = int , help = "batch size for medium length targets" ) parser . add_argument ( "-t3size" , default = 8 , type = int , help = "batch size for long targets" ) #optim parser . add_argument ( "-lr" , default = 0.1 , type = float , help = 'learning rate' ) parser . add_argument ( "-lrhigh" , default = 0.5 , type = float , help = "high learning rate for cycling" ) parser . add_argument ( "-lrstep" , default = 4 , type = int , help = 'steps in cycle' ) parser . add_argument ( "-lrwarm" , action = "store_true" , help = 'use cycling learning rate' ) parser . add_argument ( "-lrdecay" , action = "store_true" , help = "use learning rate decay" ) #parser.add_argument('-max_grad_norm', type=int, default=1) #data parser . add_argument ( "-nosave" , action = 'store_false' , help = 'dont save' ) parser . add_argument ( "-save" , required = True , help = "where to save model" ) parser . add_argument ( "-outunk" , default = 5 , type = int , help = "unk @ for targets" ) parser . add_argument ( "-entunk" , default = 5 , type = int , help = "unk @ for entity vocabulary" ) parser . add_argument ( "-datadir" , default = "data/" ) parser . add_argument ( "-data" , default = "preprocessed.train.tsv" , help = "preprocessed data" ) parser . add_argument ( "-traindata" , default = "preprocessed.train.tsv" , help = "preprocessed train data" ) parser . add_argument ( "-relvocab" , default = "relations.vocab" , type = str , help = 'vocabulary of graph relations' ) parser . add_argument ( "-savevocab" , default = None , type = str ) parser . add_argument ( "-loadvocab" , default = None , type = str ) #eval parser . add_argument ( "-eval" , action = 'store_true' ) #inference parser . add_argument ( "-max" , default = 200 , type = int , help = "max length of generation" ) parser . add_argument ( "-test" , action = 'store_true' ) #parser.add_argument("-sample",action='store_true') parser . add_argument ( "-inputs" , default = "../data/fullGraph.test.tsv" , type = str ) parser . add_argument ( "-sparse" , action = 'store_true' , help = "sparse graphs (NOT CURRENTLY IMPLEMENTED)" ) parser . add_argument ( "-plan" , action = 'store_true' , help = "plan and write (NOT IMPLEMENTED)" ) parser . add_argument ( "-ckpt" , default = None , type = str , help = 'load checkpoint' ) parser . add_argument ( "-plweight" , default = 0.2 , type = float , help = "plan weight (NOT IMPLEMENTED)" ) parser . add_argument ( "-entdetach" , action = 'store_true' , help = 'dont backprop into entity embeddings' ) parser . add_argument ( "-gpu" , default = 0 , type = int ) args = parser . parse_args ( ) if args . gpu == - 1 : args . gpu = 'cpu' args . device = torch . device ( args . gpu ) #args.options_file = "../elmo/elmo_2x2048_256_2048cnn_1xhighway_options.json" #args.weight_file = "../elmo/elmo_2x2048_256_2048cnn_1xhighway_weights.hdf5" return args