|
import torch
|
|
|
|
|
|
|
|
EXP_NAME = "IAM-339-15-E3D3-LR0.00005-bs8"; RESUME = False
|
|
|
|
DATASET = 'IAM'
|
|
if DATASET == 'IAM':
|
|
DATASET_PATHS = 'files/IAM-32.pickle'
|
|
NUM_WRITERS = 339
|
|
if DATASET == 'CVL':
|
|
DATASET_PATHS = 'files/CVL-32.pickle'
|
|
NUM_WRITERS = 283
|
|
ENGLISH_WORDS_PATH = 'files/english_words.txt'
|
|
|
|
|
|
|
|
IMG_HEIGHT = 32
|
|
resolution = 16
|
|
batch_size = 8
|
|
NUM_EXAMPLES = 15
|
|
TN_HIDDEN_DIM = 512
|
|
TN_DROPOUT = 0.1
|
|
TN_NHEADS = 8
|
|
TN_DIM_FEEDFORWARD = 512
|
|
TN_ENC_LAYERS = 3
|
|
TN_DEC_LAYERS = 3
|
|
ALPHABET = 'Only thewigsofrcvdampbkuq.A-210xT5\'MDL,RYHJ"ISPWENj&BC93VGFKz();#:!7U64Q8?+*ZX/%'
|
|
VOCAB_SIZE = len(ALPHABET)
|
|
G_LR = 0.00005
|
|
D_LR = 0.00005
|
|
W_LR = 0.00005
|
|
OCR_LR = 0.00005
|
|
EPOCHS = 100000
|
|
NUM_CRITIC_GOCR_TRAIN = 2
|
|
NUM_CRITIC_DOCR_TRAIN = 1
|
|
NUM_CRITIC_GWL_TRAIN = 2
|
|
NUM_CRITIC_DWL_TRAIN = 1
|
|
NUM_FID_FREQ = 100
|
|
|
|
DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
|
IS_SEQ = True
|
|
NUM_WORDS = 3
|
|
if not IS_SEQ: NUM_WORDS = NUM_EXAMPLES
|
|
IS_CYCLE = False
|
|
IS_KLD = False
|
|
ADD_NOISE = False
|
|
ALL_CHARS = False
|
|
SAVE_MODEL = 5
|
|
SAVE_MODEL_HISTORY = 100
|
|
|
|
def init_project():
|
|
import os, shutil
|
|
if not os.path.isdir('saved_images'): os.mkdir('saved_images')
|
|
if os.path.isdir(os.path.join('saved_images', EXP_NAME)): shutil.rmtree(os.path.join('saved_images', EXP_NAME))
|
|
os.mkdir(os.path.join('saved_images', EXP_NAME))
|
|
os.mkdir(os.path.join('saved_images', EXP_NAME, 'Real'))
|
|
os.mkdir(os.path.join('saved_images', EXP_NAME, 'Fake'))
|
|
|
|
|
