# global BATCH_SIZE
# global SHUFFLE_BUFFER_SIZE
# global IMG_SIZE
# global CHANNELS

# class hypers():
BATCH_SIZE = 256 # Big enough to measure an F1-score
SHUFFLE_BUFFER_SIZE = 1024 # Shuffle the training data by a chunck of 1024 observations
IMG_SIZE = 224 # Specify height and width of image to match the input format of the model
CHANNELS = 3 # Keep RGB color channels to match the input format of the model
LR = 1e-5 # Keep it small when transfer learning
EPOCHS = 100
LOSS_FUNCTION = "sigmoidF1"
S = -10 # sigmoid s-shape hyperparam
E = 1 # sigmoid offset hyperparam

METRIC = "macroF1"
MACRO_F1_THRESH = 0.5
LAST_ACTIVATION = "sigmoid"
IRRELEVANCE_THRESHOLD = 1000
N_LABELS_THRESHOLD = 10

FOCAL_ALPHA = 0.25
FOCAL_GAMMA = 2

# Huggingface

SUBSAMPLE = 2020

