Before iteration , i meet follow error,what should i do
and the cfg.py
import argparse
def str2bool(v):
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
else:
raise argparse.ArgumentTypeError('Boolean value expected.')
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--world-size', default=-1, type=int,
help='number of nodes for distributed training')
parser.add_argument('--rank', default=-1, type=int,
help='node rank for distributed training')
parser.add_argument('--loca_rank', default=-1, type=int,
help='node rank for distributed training')
parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='nccl', type=str,
help='distributed backend')
parser.add_argument('--seed', default=12345, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=0, type=int,
help='GPU id to use.')
parser.add_argument('--multiprocessing-distributed', action='store_true',
help='Use multi-processing distributed training to launch '
'N processes per node, which has N GPUs. This is the '
'fastest way to use PyTorch for either single node or '
'multi node data parallel training')
parser.add_argument(
'--max_epoch',
type=int,
default=200,
help='number of epochs of training')
parser.add_argument(
'--max_iter',
type=int,
default=10,
help='set the max iteration number')
parser.add_argument(
'-gen_bs',
'--gen_batch_size',
type=int,
default=4,
help='size of the batches')
parser.add_argument(
'-dis_bs',
'--dis_batch_size',
type=int,
default=4,
help='size of the batches')
parser.add_argument(
'--g_lr',
type=float,
default=0.0002,
help='adam: gen learning rate')
parser.add_argument(
'--wd',
type=float,
default=0,
help='adamw: gen weight decay')
parser.add_argument(
'--d_lr',
type=float,
default=0.0002,
help='adam: disc learning rate')
parser.add_argument(
'--ctrl_lr',
type=float,
default=3.5e-4,
help='adam: ctrl learning rate')
parser.add_argument(
'--lr_decay',
action='store_true',
help='learning rate decay or not')
parser.add_argument(
'--beta1',
type=float,
default=0.0,
help='adam: decay of first order momentum of gradient')
parser.add_argument(
'--beta2',
type=float,
default=0.9,
help='adam: decay of first order momentum of gradient')
parser.add_argument(
'--num_workers',
type=int,
default=0,
help='number of cpu threads to use during batch generation')
parser.add_argument(
'--latent_dim',
type=int,
default=128,
help='dimensionality of the latent space')
parser.add_argument(
'--img_size',
type=int,
default=256,
help='size of each image dimension')
parser.add_argument(
'--channels',
type=int,
default=3,
help='number of image channels')
parser.add_argument(
'--n_critic',
type=int,
default=1,
help='number of training steps for discriminator per iter')
parser.add_argument(
'--val_freq',
type=int,
default=20,
help='interval between each validation')
parser.add_argument(
'--print_freq',
type=int,
default=100,
help='interval between each verbose')
parser.add_argument(
'--load_path',
type=str,
help='The reload model path')
parser.add_argument(
'--exp_name',
type=str,
default='Test',
help='The name of exp')
parser.add_argument(
'--d_spectral_norm',
type=str2bool,
default=False,
help='add spectral_norm on discriminator?')
parser.add_argument(
'--g_spectral_norm',
type=str2bool,
default=False,
help='add spectral_norm on generator?')
parser.add_argument(
'--dataset',
type=str,
default='cifar10',
help='dataset type')
parser.add_argument(
'--data_path',
type=str,
default='./data',
help='The path of data set')
parser.add_argument('--init_type', type=str, default='normal',
choices=['normal', 'orth', 'xavier_uniform', 'false'],
help='The init type')
parser.add_argument('--gf_dim', type=int, default=64,
help='The base channel num of gen')
parser.add_argument('--df_dim', type=int, default=64,
help='The base channel num of disc')
parser.add_argument(
'--gen_model',
type=str,
default='ViT_custom_rp',
help='path of gen model')
parser.add_argument(
'--dis_model',
type=str,
default='ViT_custom_rp',
help='path of dis model')
parser.add_argument(
'--controller',
type=str,
default='controller',
help='path of controller')
parser.add_argument('--eval_batch_size', type=int, default=100)
parser.add_argument('--num_eval_imgs', type=int, default=50000)
parser.add_argument(
'--bottom_width',
type=int,
default=4,
help="the base resolution of the GAN")
parser.add_argument('--random_seed', type=int, default=12345)
# search
parser.add_argument('--shared_epoch', type=int, default=15,
help='the number of epoch to train the shared gan at each search iteration')
parser.add_argument('--grow_step1', type=int, default=25,
help='which iteration to grow the image size from 8 to 16')
parser.add_argument('--grow_step2', type=int, default=55,
help='which iteration to grow the image size from 16 to 32')
parser.add_argument('--max_search_iter', type=int, default=90,
help='max search iterations of this algorithm')
parser.add_argument('--ctrl_step', type=int, default=30,
help='number of steps to train the controller at each search iteration')
parser.add_argument('--ctrl_sample_batch', type=int, default=1,
help='sample size of controller of each step')
parser.add_argument('--hid_size', type=int, default=100,
help='the size of hidden vector')
parser.add_argument('--baseline_decay', type=float, default=0.9,
help='baseline decay rate in RL')
parser.add_argument('--rl_num_eval_img', type=int, default=5000,
help='number of images to be sampled in order to get the reward')
parser.add_argument('--num_candidate', type=int, default=10,
help='number of candidate architectures to be sampled')
parser.add_argument('--topk', type=int, default=5,
help='preserve topk models architectures after each stage' )
parser.add_argument('--entropy_coeff', type=float, default=1e-3,
help='to encourage the exploration')
parser.add_argument('--dynamic_reset_threshold', type=float, default=1e-3,
help='var threshold')
parser.add_argument('--dynamic_reset_window', type=int, default=500,
help='the window size')
parser.add_argument('--arch', nargs='+', type=int,
help='the vector of a discovered architecture')
parser.add_argument('--optimizer', type=str, default="adam",
help='optimizer')
parser.add_argument('--loss', type=str, default="hinge",
help='loss function')
parser.add_argument('--n_classes', type=int, default=0,
help='classes')
parser.add_argument('--phi', type=float, default=1,
help='wgan-gp phi')
parser.add_argument('--grow_steps', nargs='+', type=int,default=[50,100,150],
help='the vector of a discovered architecture')
parser.add_argument('--D_downsample', type=str, default="avg",
help='downsampling type')
parser.add_argument('--fade_in', type=float, default=1,
help='fade in step')
parser.add_argument('--d_depth', type=int, default=7,
help='Discriminator Depth')
parser.add_argument('--g_depth', type=str, default="5,4,2",
help='Generator Depth')
parser.add_argument('--g_norm', type=str, default="ln",
help='Generator Normalization')
parser.add_argument('--d_norm', type=str, default="ln",
help='Discriminator Normalization')
parser.add_argument('--g_act', type=str, default="gelu",
help='Generator activation Layer')
parser.add_argument('--d_act', type=str, default="gelu",
help='Discriminator activation layer')
parser.add_argument('--patch_size', type=int, default=4,
help='Discriminator Depth')
parser.add_argument('--fid_stat', type=str, default="./fid_stat/fid_camera.npz",
help='Discriminator Depth')
parser.add_argument('--diff_aug', type=str, default="None",
help='differentiable augmentation type')
parser.add_argument('--accumulated_times', type=int, default=1,
help='gradient accumulation')
parser.add_argument('--g_accumulated_times', type=int, default=1,
help='gradient accumulation')
parser.add_argument('--num_landmarks', type=int, default=64,
help='number of landmarks')
parser.add_argument('--d_heads', type=int, default=4,
help='number of heads')
parser.add_argument('--dropout', type=float, default=0.,
help='dropout ratio')
parser.add_argument('--ema', type=float, default=0.995,
help='ema')
parser.add_argument('--ema_warmup', type=float, default=0.,
help='ema warm up')
parser.add_argument('--ema_kimg', type=int, default=500,
help='ema thousand images')
parser.add_argument('--latent_norm',action='store_true',
help='latent vector normalization')
parser.add_argument('--ministd',action='store_true',
help='mini batch std')
parser.add_argument('--g_mlp', type=int, default=4,
help='generator mlp ratio')
parser.add_argument('--d_mlp', type=int, default=4,
help='discriminator mlp ratio')
parser.add_argument('--g_window_size', type=int, default=8,
help='generator mlp ratio')
parser.add_argument('--d_window_size', type=int, default=8,
help='discriminator mlp ratio')
parser.add_argument('--show', action='store_true',
help='show')
opt = parser.parse_args()
return opt
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