CIPL/settings.py at master · cwangrun/CIPL · GitHub

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base_architecture = 'densenet121'
img_size = 512
num_classes = 15
prototype_shape = (50 * num_classes, 256, 1, 1)
prototype_activation_function = 'log'
add_on_layers_type = 'regular'
experiment_run = str(img_size)

root_dir = '/mnt/c/chong/data/chestxray/'

train_batch_size = 24          # 24
test_batch_size = 64           # 200
train_push_batch_size = 20     # 100


lr_reduce_factor = 0.5
lr_backbone = 1e-4
lr = 3e-3


joint_optimizer_lrs = {'features': lr_backbone,
                       'add_on_layers': lr,
                       'prototype_vectors': lr}
joint_lr_step_size = 5

warm_optimizer_lrs = {'add_on_layers': lr,
                      'prototype_vectors': lr}

last_layer_optimizer_lr = 1e-4

coefs = {
    'crs_ent': 1,
    'clst': 0.02,
    'sep': 0.02,
    'cross_att': 0.5,
    'inte_align': 0.5,
    'pred_align': 10,
}

num_train_epochs = 41
num_warm_epochs = 15

push_start = 35
push_epochs = [i for i in range(num_train_epochs) if i % 5 == 0]