:W&BKM 2fji5j4w; 9 /0.29.0+7872fd9d9f86ca5c50617e19cb168122b7f959480.70.0." ry4aai5nw8mc 2fji5j4w 2fji5j4wjuju11-uc-san-diegoSPAtop" _wandb{}  batch_size1024  dataset_limit0.2  dropout0.21672731014814187 epochs10  hidden_dim256 ' learning_rate0.0011195114676798622  num_attention_heads8  num_branch_encoder_layers5  num_embedding_layers10  num_encoder_layers6Bjjtttt_vanilla_2fji5j4wb88oquqqwj)jj-spatop-sweepagent-tttt-vanilla-2-spfhc ؐ3 (Hhp"3.12.10*0.29.0j linux-x86_645;7 2fji5j4w&  _runtime0  _wandb.runtime0 ]j -Linux-6.8.0-136-generic-x86_64-with-glibc2.36CPython 3.12.10 ϴ*-of*=/data/spatop/options_files/sweep_tttt_jj/config_2fji5j4w.json*-l* /scratch/logs*-n*jjtttt_vanilla_2fji5j4w2-m spanet.trainRjacksonjulian2014@gmail.comZ /scratch/logsb)jj-spatop-sweepagent-tttt-vanilla-2-spfhcr/opt/conda/bin/python hw73dpphyyqmhrhmiyowav2bojdc5w448jNVIDIA A100-SXM4-80GB /.ۑ!ӽS NVIDIA A100-SXM4-80GB6"Ampere*(GPU-1512559d-7724-700d-39a3-dab660c9a52e13.3 hw73dpphyyqmhrhmiyowav2bojdc5w442  requirements.txt W 2fji5j4wZF (H (H (hp"3.12.10*0.29.0j linux-x86_64*G8PY 2fji5j4wZH (H (H (8hp"3.12.10*0.29.0j linux-x86_64&* 2fji5j4wb trainer/global_step2O!\ 2fji5j4wZK (H (H(8hp"3.12.10*0.29.0j linux-x86_64/ 2fji5j4wb*"trainer/global_step2K 2fji5j4wj: *LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0] 1o 2fji5j4wj  А ┏━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━┓ ┃ ┃ Name ┃ Type ┃ Params ┃ Mode ┃ FLOPs ┃ ┡━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━┩ │ 0 │ embedding │ MultiInputVectorEmbed… │ 3.4 M │ train │ 0 │ │ 1 │ encoder │ JetEncoder │ 7.9 M │ train │ 0 │ │ 2 │ branch_decoders │ ModuleList │ 183 M │ train │ 0 │ │ 3 │ regression_decoder │ RegressionDecoder │ 0 │ train │ 0 │ │ 4 │ classification_decoder │ ClassificationDecoder │ 0 │ train │ 0 │ │ │ other params │ n/a │ 48 │ n/a │ n/a │ └───┴────────────────────────┴────────────────────────┴────────┴───────┴───────┘ YHJ\ 2fji5j4wj ЮTrainable params: 194 M Non-trainable params: 86 Total params: 194 M Total estimated model params size (MB): 777.876 Modules in train mode: 5157 Modules in eval mode: 0 Total FLOPs: 0 ,q 2fji5j4wj` Pwandb: WARNING Config item 'hidden_dim' was locked by 'sweep' (ignored update). $D{ 2fji5j4wjj Zwandb: WARNING Config item 'num_embedding_layers' was locked by 'sweep' (ignored update). c#y 2fji5j4wjh Xwandb: WARNING Config item 'num_encoder_layers' was locked by 'sweep' (ignored update). ^` 2fji5j4wjo _wandb: WARNING Config item 'num_branch_encoder_layers' was locked by 'sweep' (ignored update). N0z 2fji5j4wji Ywandb: WARNING Config item 'num_attention_heads' was locked by 'sweep' (ignored update). \!At 2fji5j4wjc Swandb: WARNING Config item 'dataset_limit' was locked by 'sweep' (ignored update). ?q 2fji5j4wj` Pwandb: WARNING Config item 'batch_size' was locked by 'sweep' (ignored update). Ft 2fji5j4wjc Swandb: WARNING Config item 'learning_rate' was locked by 'sweep' (ignored update). z", line 198, in _run_module_as_main %.9$ 2fji5j4wj Ӵ}P% 2fji5j4wj? ܴ/ File "", line 88, in _run_code & 2fji5j4wj Iy' 2fji5j4wjh X File "/opt/conda/lib/python3.12/site-packages/spanet/train.py", line 277, in 6Y( 2fji5j4wj IV%) 2fji5j4wj ɔ )vE* 2fji5j4wj4 $main(**parser.parse_args().__dict__);_"+ 2fji5j4wj 柵 |, 2fji5j4wj ۝u- 2fji5j4wjd ҫT File "/opt/conda/lib/python3.12/site-packages/spanet/train.py", line 207, in main . 2fji5j4wj e%/ 2fji5j4wj Ƶ cAI0 2fji5j4wj8 اε(trainer.fit(model, ckpt_path=checkpoint)8 9"1 2fji5j4wj ҵ &oA2 2fji5j4wj ۵U3 2fji5j4wjx h File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 584, in fit N4 2fji5j4wj  #%5 2fji5j4wj  VgCA6 2fji5j4wj0  call._call_and_handle_interrupt(c?"7 2fji5j4wj ͅ s8 2fji5j4wj 裓9 2fji5j4wj 蔘{ File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/call.py", line 49, in _call_and_handle_interrupt : 2fji5j4wj Sg%; 2fji5j4wj  MC< 2fji5j4wj2 "return trainer_fn(*args, **kwargs)N 4"= 2fji5j4wj  Ͳ6> 2fji5j4wj ¶Pv+j"? 2fji5j4wj Ƕ S"@ 2fji5j4wj ˶ q"A 2fji5j4wj ζ ћ."B 2fji5j4wj Զ $"C 2fji5j4wj ٶ b"D 2fji5j4wj ߶ :"E 2fji5j4wj  IUR"F 2fji5j4wj  /2"G 2fji5j4wj  :!"H 2fji5j4wj  "I 2fji5j4wj  )"J 2fji5j4wj ^="K 2fji5j4wj ^ȿ"L 2fji5j4wj 䊷^ẹ"M 2fji5j4wj Ə^=]n"N 2fji5j4wj ܟ^C"O 2fji5j4wj ࣷ^"P 2fji5j4wj ڪ^%"Q 2fji5j4wj ۯ^ t"R 2fji5j4wj ^D߼"S 2fji5j4wj ^Q "T 2fji5j4wj ·^WԜ"U 2fji5j4wj Ʒ^.^"V 2fji5j4wj ʷ^qi"W 2fji5j4wj з^hv"X 2fji5j4wj Է^%j"Y 2fji5j4wj ڷ^3"Z 2fji5j4wj ޷^j"[ 2fji5j4wj ^&3P"\ 2fji5j4wj ^HM||"] 2fji5j4wj ^@+"^ 2fji5j4wj ^?"_ 2fji5j4wj ^c}f"` 2fji5j4wj ^b"a 2fji5j4wj ^T6"b 2fji5j4wj ؆^r"c 2fji5j4wj ȇ^D"d 2fji5j4wj ᐸ^[;"e 2fji5j4wj  *|f 2fji5j4wj .g 2fji5j4wj~ n File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 630, in _fit_impl w`th 2fji5j4wj ȆŌ%i 2fji5j4wj Л yāaj 2fji5j4wjP ĸ@self._run(model, ckpt_path=ckpt_path, weights_only=weights_only)"k 2fji5j4wj θ |l 2fji5j4wj ָŋm 2fji5j4wjz ܸj File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 1079, in _run An 2fji5j4wj ؽn%o 2fji5j4wj  V<p 2fji5j4wj+ results = self._run_stage()v"q 2fji5j4wj ȭ nr 2fji5j4wj й-"s 2fji5j4wj 虷 s"t 2fji5j4wj  Z"u 2fji5j4wj ت ?k"v 2fji5j4wj ȹ W"w 2fji5j4wj ι ""x 2fji5j4wj չ "y 2fji5j4wj ٹ {"z 2fji5j4wj  Ȍ"{ 2fji5j4wj  "| 2fji5j4wj  ^"} 2fji5j4wj  Xq"~ 2fji5j4wj ȷ [)>" 2fji5j4wj   # 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