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