EricGu1001
commented
1 month ago
(calm) (base) penghuan@ubuntu:~/code/SimSGT/regression$ sh script/pretrain_GEOM.sh
add args
Namespace(batch_size=2048, block_mask=False, block_size=2, brics_pooling='mean', complete_feature=True, custom_trans=True, d_model=128, dataset='GEOM/GEOM_3D_nmol100_nconf5_nupper1000_morefeat', decay=0, decoder_input_norm=True, decoder_jk='last', device=0, dim_feedforward=512, dim_pe=28, disable_remask=False, drop_mask_tokens=True, eigvec_norm='L2', epochs=100, eps=0.5, gnn_JK='last', gnn_activation='relu', gnn_decoder_layer=3, gnn_dropout=0, gnn_emb_dim=300, gnn_encoder_layer=5, gnn_norm='batchnorm', gnn_token_layer=1, gnn_type='gin_v3', input_model_file=None, kernel_times=[], kernel_times_func='none', laplacian_norm='none', layers=3, log_steps=100, loss='mse', loss_all_nodes=False, lr=0.001, mask_rate=0.35, max_freqs=20, model_file=None, model_save_prefix='model', moving_average_decay=0.99, name='pretrain_GEOM', nhead=4, no_edge_tokenizer=False, nonpara_tokenizer=True, num_workers=4, optim_file=None, pe_type='none', phi_hidden_dim=32, phi_out_dim=32, post_layers=2, pretrained_tokenizer=False, raw_norm_type='none', resume_epoch=0, save_epochs=20, seed=42, split=None, subgraph_mask=False, tk_JK='last', tk_activation='relu', tk_decoder_JK='last', tk_decoder_layers=1, tk_decoder_remask=False, tk_dropout=0, tk_full_x=False, tk_gnn_type='gin', tk_layers=1, tk_no_edge=False, tk_no_edge_decoder=False, tk_pretrain_scheme='graphmae', tk_trans_layers=0, tlr_scale=1.0, tokenizer_path=None, tokenizer_type='gin', trans_decoder_layer=1, trans_encoder_layer=4, transformer_activation='relu', transformer_dropout=0, transformer_norm_input=True, use_trans_decoder=True, zero_mask=False)
[2024-07-14 01:10:05] Namespace(batch_size=2048, block_mask=False, block_size=2, brics_pooling='mean', complete_feature=True, custom_trans=True, d_model=128, dataset='GEOM/GEOM_3D_nmol100_nconf5_nupper1000_morefeat', decay=0, decoder_input_norm=True, decoder_jk='last', device=device(type='cuda', index=0), dim_feedforward=512, dim_pe=28, disable_remask=False, drop_mask_tokens=True, eigvec_norm='L2', epochs=100, eps=0.5, gnn_JK='last', gnn_activation='relu', gnn_decoder_layer=3, gnn_dropout=0, gnn_emb_dim=300, gnn_encoder_layer=5, gnn_norm='batchnorm', gnn_token_layer=1, gnn_type='gin_v3', input_model_file=None, kernel_times=[], kernel_times_func='none', laplacian_norm='none', layers=3, log_file='./results/pretrain_GEOM/log.txt', log_steps=100, loss='mse', loss_all_nodes=False, lr=0.001, mask_rate=0.35, max_freqs=20, model_file=None, model_save_prefix='model', moving_average_decay=0.99, name='pretrain_GEOM', nhead=4, no_edge_tokenizer=False, nonpara_tokenizer=True, num_workers=4, optim_file=None, pe_type='none', phi_hidden_dim=32, phi_out_dim=32, post_layers=2, pretrained_tokenizer=False, raw_norm_type='none', resume_epoch=0, save_epochs=20, seed=42, split=None, subgraph_mask=False, tk_JK='last', tk_activation='relu', tk_decoder_JK='last', tk_decoder_layers=1, tk_decoder_remask=False, tk_dropout=0, tk_full_x=False, tk_gnn_type='gin', tk_layers=1, tk_no_edge=False, tk_no_edge_decoder=False, tk_pretrain_scheme='graphmae', tk_trans_layers=0, tlr_scale=1.0, tokenizer_path=None, tokenizer_type='gin', trans_decoder_layer=1, trans_encoder_layer=4, transformer_activation='relu', transformer_dropout=0, transformer_norm_input=True, use_trans_decoder=True, zero_mask=False)
Traceback (most recent call last):
File "pretraining.py", line 168, in