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25 lines
603 B
Python
25 lines
603 B
Python
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import albumentations as A
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import cv2
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import torch
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from math import log2
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from albumentations.pytorch import ToTensorV2
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#from utils import seed_everything
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START_TRAIN_AT_IMG_SIZE = 32
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DATASET = 'FFHQ_32'
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CHECKPOINT_GEN = "generator.pth"
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CHECKPOINT_CRITIC = "critic.pth"
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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LOAD_MODEL = False
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SAVE_MODEL = True
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LEARNING_RATE = 1e-3
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BATCH_SIZES = [32, 32, 32, 32, 32, 16, 8, 4, 2]
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CHANNELS_IMG = 3
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Z_DIM = 512
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W_DIM = 512
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IN_CHANNELS = 512
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LAMBDA_GP = 10
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PROGRESSIVE_EPOCHS = [50] * 100
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FIXED_NOISE = torch.randn((8, Z_DIM)).to(DEVICE)
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NUM_WORKERS = 6
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