def main():
    '"options for criterion is wasserstien, h_divergence'
    itertn = 1
    c3_value = 0.5
    for trial in range(1):
        args = {'img_size': 28, 'chnnl': 1, 'lr': 0.01, 'momentum': 0.9, 'epochs': 1, 'tr_smpl': 1000, 'test_smpl': 10000, 'tsk_list': ['mnist', 'svhn', 'm_mnist'], 'grad_weight': 1, 'Trials': trial, 'criterion': 'wasserstien', 'c3': c3_value}
        ft_extrctor_prp = {'layer1': {'conv': [1, 32, 5, 1, 2], 'elu': [], 'maxpool': [3, 2, 0]}, 'layer2': {'conv': [32, 64, 5, 1, 2], 'elu': [], 'maxpool': [3, 2, 0]}}
        hypoth_prp = {'layer3': {'fc': [util.in_feature_size(ft_extrctor_prp, args['img_size']), 128], 'act_fn': 'elu'}, 'layer4': {'fc': [128, 10], 'act_fn': 'softmax'}}
        discrm_prp = {'reverse_gradient': {}, 'layer3': {'fc': [util.in_feature_size(ft_extrctor_prp, args['img_size']), 128], 'act_fn': 'elu'}, 'layer4': {'fc': [128, 1], 'act_fn': 'sigm'}}
        mtl = MTL_pairwise(ft_extrctor_prp, hypoth_prp, discrm_prp, **args)
        del mtl
"options for criterion is wasserstien, h_divergence
def main():
    
    itertn = 1
    c3_value = 0.5
    for trial in range(1):
        args = {'img_size': 28, 'chnnl': 1, 'lr': 0.01, 'momentum': 0.9, 'epochs': 1, 'tr_smpl': 1000, 'test_smpl': 10000, 'tsk_list': ['mnist', 'svhn', 'm_mnist'], 'grad_weight': 1, 'Trials': trial, 'criterion': 'wasserstien', 'c3': c3_value}
        ft_extrctor_prp = {'layer1': {'conv': [1, 32, 5, 1, 2], 'elu': [], 'maxpool': [3, 2, 0]}, 'layer2': {'conv': [32, 64, 5, 1, 2], 'elu': [], 'maxpool': [3, 2, 0]}}
        hypoth_prp = {'layer3': {'fc': [util.in_feature_size(ft_extrctor_prp, args['img_size']), 128], 'act_fn': 'elu'}, 'layer4': {'fc': [128, 10], 'act_fn': 'softmax'}}
        discrm_prp = {'reverse_gradient': {}, 'layer3': {'fc': [util.in_feature_size(ft_extrctor_prp, args['img_size']), 128], 'act_fn': 'elu'}, 'layer4': {'fc': [128, 1], 'act_fn': 'sigm'}}
        mtl = MTL_pairwise(ft_extrctor_prp, hypoth_prp, discrm_prp, **args)
        del mtl