import torch.nn.functional as F
import torch_geometric
hps = {
 'Runtime': 77,
 'NLL_eps': 2.436197459304298e-10,
 'add_pool': True,
 'afp_dropout': 0.7725915228072406,
 'attentionlayer_size': 330,
 'bs': 39,
 'cutoff': 1.8707988760248344,
 'dnn_activation': F.leaky_relu,
 'embedding_size': 284,
 'gnn_activation': F.relu,
 'gnn_heads': 4,
 'gnn_hl_size': 69,
 'gnn_layer_type': torch_geometric.nn.conv.gcn_conv.GCNConv,
 'gnn_output_size': 511,
 'hl_dropout': 0.0013470124983784,
 'hl_size': 789,
 'lr': 0.0003641888380695,
 'max_pool': True,
 'mean_pool': True,
 'mol_add_pool': True,
 'mol_gnn_activation': F.relu,
 'mol_gnn_heads': 3,
 'mol_gnn_hl_size': 69,
 'mol_gnn_layer_type': torch_geometric.nn.conv.cg_conv.CGConv,
 'mol_gnn_output_size': 197,
 'mol_max_pool': True,
 'mol_mean_pool': True,
 'mol_u_net_type': True,
 'num_afp_layers': 1,
 'num_gnn_hl': 3,
 'num_gnn_layers': 6,
 'num_hl': 18,
 'num_mol_gnn_hl': 3,
 'num_mol_gnn_layers': 10,
 'num_timesteps': 4,
 'optimizer': 'Adam',
 'seperated_dnn': False,
 'triangle': False,
 'u_net_type': True,
 'weight_decay': 5.767421398641679e-10,
 'final loss': -4.5379414558410645,
 'final mae': 0.0016728639602661,
 'val loss': -4.5379414558410645,
 'val mae': 0.0016728639602661
 }

random_states = {1:0,
                 2:1,
                 3:7,
                 4:13,
                 5:42,
                 6:69,
                 7:1337,
                 8:1996,
                 9:2022,
                 10:9000}

random_states_ccsdt = {1:0,
                    2:1,
                    3:7,
                    4:13,
                    5:42,
                    6:1111,
                    7:1337,
                    8:2022,
                    9:2222,
                    10:9000}