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from pydantic_settings import BaseSettings | |
class Config(BaseSettings): | |
IMAGE_CHANNEL: int = 3 | |
LABEL_CHANNEL: int = 3 | |
NUM_CLASSES: int = 3 | |
IMAGE_SIZE: int = 128 | |
FEATURES_DISCRIMINATOR: int = 64 * 2 | |
FEATURES_GENERATOR: int = 64 * 2 | |
EMBED_SIZE: int = 30 + 20 | |
INPUT_Z_DIM: int = 64 * 2 | |
BATCH_SIZE: int = 20 | |
DISPLAY_STEP: int = 500 | |
MAX_SAMPLES: int = 2500 | |
LEARNING_RATE: float = 0.0002 | |
BETA_1: float = 0.5 | |
BETA_2: float = 0.999 | |
C_LAMBDA: int = 10 | |
NUM_EPOCH: int = 200 * 5 | |
CRITIC_REPEAT: int = 3 | |
LOAD_CHECKPOINT: bool = True | |
PATH_DATASET: str = "/kaggle/input/shoe-vs-sandal-vs-boot-dataset-15k-images/Shoe vs Sandal vs Boot Dataset" | |
CKPT_PATH: str = "./weights/epoch=299-step=450000.ckpt" | |
OPTIONS_MAPPING: dict = { | |
"Boot": 0, | |
"Sandal": 1, | |
"Shoe": 2 | |
} | |
config = Config() |