:W&B7&M 7gj9dgxm; 9 /0.29.0+7872fd9d9f86ca5c50617e19cb168122b7f959480.70.0sd" jxfgywjc1cdt 7gj9dgxm 7gj9dgxmjuju11-uc-san-diegoSPAtop" _wandb{}  batch_size1024  dataset_limit0.2  dropout0.2675228023058011 epochs10  hidden_dim256 ' learning_rate0.0004972925297807339  num_attention_heads4  num_branch_encoder_layers7  num_embedding_layers6  num_encoder_layers4Bjjtttt_blocks_7gj9dgxmbs2s2ev0zj*jj-spatop-sweepagent-tttt-pairwise-1-8pwgv ȁ3 (Hhp"3.12.10*0.29.0j linux-x86_64+-7 7gj9dgxm&  _runtime0  _wandb.runtime0j -Linux-6.8.0-137-generic-x86_64-with-glibc2.36CPython 3.12.10 *-of*=/data/spatop/options_files/sweep_tttt_jj/config_7gj9dgxm.json*-l* /scratch/logs*-n*jjtttt_blocks_7gj9dgxm2-m spanet.trainRjacksonjulian2014@gmail.comZ /scratch/logsb*jj-spatop-sweepagent-tttt-pairwise-1-8pwgvr/opt/conda/bin/python o4ukllvzfd5qqfpizh8x22x85s08cb79INVIDIA A100-SXM4-80GB /oUS NVIDIA A100-SXM4-80GB6"Ampere*(GPU-c1fdb213-5a16-84e3-13b4-cf29bc35dbf813.2 o4ukllvzfd5qqfpizh8x22x85s08cb792  requirements.txt^1W 7gj9dgxmZF (H (H (hp"3.12.10*0.29.0j linux-x86_64Y 7gj9dgxmZH (H (H (8hp"3.12.10*0.29.0j linux-x86_64eU* 7gj9dgxmb trainer/global_step2n#\ 7gj9dgxmZK (H (H(8hp"3.12.10*0.29.0j linux-x86_64㦉Y/ 7gj9dgxmb*"trainer/global_step20TJ 7gj9dgxmj9 讲h*LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]  7gj9dgxmj   ┏━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━┓ ┃ ┃ Name ┃ Type ┃ Params ┃ Mode ┃ FLOPs ┃ ┡━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━┩ │ 0 │ embedding │ MultiInputVectorEmbed… │ 3.4 M │ train │ 0 │ │ 1 │ encoder │ JetEncoderWithPairwise │ 5.3 M │ train │ 0 │ │ 2 │ branch_decoders │ ModuleList │ 214 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 │ └───┴────────────────────────┴────────────────────────┴────────┴───────┴───────┘ 0*\ 7gj9dgxmj Trainable params: 223 M Non-trainable params: 86 Total params: 223 M Total estimated model params size (MB): 893.649 Modules in train mode: 5866 Modules in eval mode: 0 Total FLOPs: 0 ~#^q 7gj9dgxmj` Pwandb: WARNING Config item 'hidden_dim' was locked by 'sweep' (ignored update). 9!{ 7gj9dgxmjj Zwandb: WARNING Config item 'num_embedding_layers' was locked by 'sweep' (ignored update). y 7gj9dgxmjh Xwandb: WARNING Config item 'num_encoder_layers' was locked by 'sweep' (ignored update). fX% 7gj9dgxmjo _wandb: WARNING Config item 'num_branch_encoder_layers' was locked by 'sweep' (ignored update). z 7gj9dgxmji Ywandb: WARNING Config item 'num_attention_heads' was locked by 'sweep' (ignored update). ܷt 7gj9dgxmjc ŠSwandb: WARNING Config item 'dataset_limit' was locked by 'sweep' (ignored update). lg2q 7gj9dgxmj` Pwandb: WARNING Config item 'batch_size' was locked by 'sweep' (ignored update). t 7gj9dgxmjc Swandb: WARNING Config item 'learning_rate' was locked by 'sweep' (ignored update). hn 7gj9dgxmj] Mwandb: WARNING Config item 'dropout' was locked by 'sweep' (ignored update). Mm 7gj9dgxmj\ Lwandb: WARNING Config item 'epochs' was locked by 'sweep' (ignored update). Z 7gj9dgxm*  transformer_dim256  transformer_dim_scale2.0  initial_embedding_dim256  position_embedding_dim256 ! num_branch_embedding_layers3  num_jet_embedding_layers0  num_jet_encoder_layers2  num_detector_layers2  num_regression_layers3  num_classification_layers3  split_symmetric_attention1 ! transformer_activation"gelu"  skip_connections1 ( "initial_embedding_skip_connections1  linear_block_type"GRU"  transformer_type"Gated"  linear_activation"gelu"  normalization "LayerNorm"  masking "Filling" linear_prelu_activationtrue  use_pairwise_interactions1  num_pairwise_features4  pairwise_embedding_dim8  pairwise_input_source"all"  pairwise_block_embeddings1  pairwise_cross_typetrue  pairwise_feature_set""  pairwise_eq2to2false  use_moefalse  num_experts8  num_experts_per_tok2  moe_loss_scale0.01 F event_info_file2"/data/spatop/event_files/tttt/tttt_hadronic.yaml" = training_file+"/data/spatop/tttt_15M/h5/tttt_training.h5"  validation_file""  testing_file""  normalize_features1  limit_to_num_jets0  balance_particles0  balance_jets0 ! balance_classificationsfalse  partial_events1  dataset_randomization0  train_validation_split0.95  limit_val_batches1.0  num_dataloader_workers0  mask_sequence_vectors1  combine_pair_loss"min"  optimizer"AdamW"  focal_gamma0.0  combinatorial_scale0.0 # learning_rate_warmup_epochs1.0  learning_rate_cycles1  assignment_loss_scale1.0  detection_loss_scale1.0  kl_loss_scale0.0  regression_loss_scale0.0 ! classification_loss_scale0.0 ! use_mass_classificationfalse  mass_classes[]  balance_lossestrue  l2_penalty0.0002  gradient_clip10.0 num_gpu1  verbose_outputfalse  usable_gpus""  trial_time"" $ trial_output_dir"./test_output" 7gj9dgxmj Ƽ/opt/conda/lib/python3.12/site-packages/pytorch_lightning/utilities/_pytree.py:21: `isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead. 0jBN 7gj9dgxmj ؂/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:434: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=3` in the `DataLoader` to improve performance. Нy 7gj9dgxmj ӕ/opt/conda/lib/python3.12/site-packages/pytorch_lightning/utilities/_pytree.py:21: `isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead. P 7gj9dgxmj /opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:434: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=3` in the `DataLoader` to improve performance. 6}!u 7gj9dgxmjd REpoch 0/9 0/302 0:00:01 • -:--:-- 0.00it/s v_num: dgxm;$ 7gj9dgxmj  En 7gj9dgxmj tfD! 7gj9dgxmj3 ʷ#Traceback (most recent call last): B\" 7gj9dgxmj Ϸ[# 7gj9dgxmjJ ҷ: File "", line 198, in _run_module_as_main +$ 7gj9dgxmj ַ>,_mP% 7gj9dgxmj? ٷ/ File "", line 88, in _run_code 0& 7gj9dgxmj ܷ+y' 7gj9dgxmjh ȎX File "/opt/conda/lib/python3.12/site-packages/spanet/train.py", line 277, in ( 7gj9dgxmj 4%) 7gj9dgxmj  hE* 7gj9dgxmj4 $main(**parser.parse_args().__dict__)bZ"+ 7gj9dgxmj  ^, 7gj9dgxmj ؘǹCRu- 7gj9dgxmjd ϹT File "/opt/conda/lib/python3.12/site-packages/spanet/train.py", line 207, in main s. 7gj9dgxmj &:u%/ 7gj9dgxmj  <քI0 7gj9dgxmj8 (trainer.fit(model, ckpt_path=checkpoint)/"1 7gj9dgxmj  h2 7gj9dgxmj 𵎺U;3 7gj9dgxmjx h File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 584, in fit wp4 7gj9dgxmj пi%5 7gj9dgxmj β `A6 7gj9dgxmj0  call._call_and_handle_interrupt(A"7 7gj9dgxmj  y!8 7gj9dgxmj ĺ# *9 7gj9dgxmj ،Ⱥ{ File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/call.py", line 49, in _call_and_handle_interrupt \NU: 7gj9dgxmj ݺPW%; 7gj9dgxmj  DUC< 7gj9dgxmj2 "return trainer_fn(*args, **kwargs) r"= 7gj9dgxmj  <> 7gj9dgxmj r"? 7gj9dgxmj  c"@ 7gj9dgxmj 诀 H"A 7gj9dgxmj  #tR"B 7gj9dgxmj  "C 7gj9dgxmj  d"D 7gj9dgxmj 𸊻 :C"E 7gj9dgxmj  ="F 7gj9dgxmj خ ="G 7gj9dgxmj  ]r"H 7gj9dgxmj ޕ CH"I 7gj9dgxmj ؖ )8"J 7gj9dgxmj 暻^wi&"K 7gj9dgxmj Ɲ^"L 7gj9dgxmj ^@>"M 7gj9dgxmj ֢^ "N 7gj9dgxmj ^_u"O 7gj9dgxmj ^""P 7gj9dgxmj ^$"Q 7gj9dgxmj ^\="R 7gj9dgxmj ޯ^4}"S 7gj9dgxmj Ų^."T 7gj9dgxmj ^("U 7gj9dgxmj 巻^_"V 7gj9dgxmj ح^V"W 7gj9dgxmj ^܉h"X 7gj9dgxmj û^iNd"Y 7gj9dgxmj ƻ^J"Z 7gj9dgxmj ɻ^``g"[ 7gj9dgxmj ͻ^r"\ 7gj9dgxmj ϻ^2""] 7gj9dgxmj һ^2"^ 7gj9dgxmj вջ^zc"_ 7gj9dgxmj Ȃػ^"` 7gj9dgxmj ڻ^&"a 7gj9dgxmj ݻ^*J "b 7gj9dgxmj ߻^)"c 7gj9dgxmj ^?ֹ"d 7gj9dgxmj ^ɍ"e 7gj9dgxmj  :xf 7gj9dgxmj ! g 7gj9dgxmj~ n File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 630, in _fit_impl &h 7gj9dgxmj П6g%i 7gj9dgxmj  f Jaj 7gj9dgxmjP Ȣ@self._run(model, ckpt_path=ckpt_path, weights_only=weights_only)"k 7gj9dgxmj  q l 7gj9dgxmj `m 7gj9dgxmjz ۝j File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 1079, in _run qi2n 7gj9dgxmj  ?!%o 7gj9dgxmj ½ -D<p 7gj9dgxmj+ ɽresults = self._run_stage()["q 7gj9dgxmj ֽ tHr 7gj9dgxmj d"s 7gj9dgxmj  $L"t 7gj9dgxmj  Z'"u 7gj9dgxmj  8J"v 7gj9dgxmj  cI"w 7gj9dgxmj  1$F"x 7gj9dgxmj Ё &x"y 7gj9dgxmj 𯄾 hJ|"z 7gj9dgxmj  Dy"{ 7gj9dgxmj  +"| 7gj9dgxmj 鋾 ź#"} 7gj9dgxmj  -"~ 7gj9dgxmj  "F" 7gj9dgxmj ȹ 77# 7gj9dgxmj  hI# 7gj9dgxmj ˜^(n# 7gj9dgxmj ^/l# 7gj9dgxmj ҝ^- # 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7gj9dgxmj ^ D# 7gj9dgxmj  MM;  7gj9dgxmj ࡏ}֚ 7gj9dgxmj w File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/strategies/strategy.py", line 239, in optimizer_step }b  7gj9dgxmj o& 7gj9dgxmj  /)X 7gj9dgxmjn ^return self.precision_plugin.optimizer_step(optimizer, model=model, closure=closure, **kwargs)u# 7gj9dgxmj  IAb  7gj9dgxmj BI# 7gj9dgxmj ؓ  g# 7gj9dgxmj  B# 7gj9dgxmj  0# 7gj9dgxmj  8њ# 7gj9dgxmj  !-h# 7gj9dgxmj  # 7gj9dgxmj  # 7gj9dgxmj  ᾑ# 7gj9dgxmj  jK# 7gj9dgxmj  ͷB# 7gj9dgxmj  Cv R# 7gj9dgxmj Е^J"# 7gj9dgxmj ^-# 7gj9dgxmj ^qz# 7gj9dgxmj ^+_# 7gj9dgxmj ^w# 7gj9dgxmj ^ /# 7gj9dgxmj ^t'C# 7gj9dgxmj ^ # 7gj9dgxmj ^Ckp# 7gj9dgxmj ^ޮ}# 7gj9dgxmj 迏^3)8# 7gj9dgxmj ^q# 7gj9dgxmj Ȕ^t 1# 7gj9dgxmj Я^,# 7gj9dgxmj ^i# 7gj9dgxmj ^wH# 7gj9dgxmj Ԣ^؍# 7gj9dgxmj Ѕ^J!*# 7gj9dgxmj ^1t # 7gj9dgxmj ^ P# 7gj9dgxmj ^0ds# 7gj9dgxmj Ȯ^ # 7gj9dgxmj ^# 7gj9dgxmj ؝^+# 7gj9dgxmj Δ^(g"# 7gj9dgxmj ^=# 7gj9dgxmj ^ĩT# 7gj9dgxmj ^'# 7gj9dgxmj ^횞 # 7gj9dgxmj ȟ^Nԙ# 7gj9dgxmj У^u# 7gj9dgxmj ^I*A# 7gj9dgxmj ^WgQ# 7gj9dgxmj ^.^S# 7gj9dgxmj Т^+}## 7gj9dgxmj ۯ^A# 7gj9dgxmj Г^Dʀ# 7gj9dgxmj Ӵ^aO# 7gj9dgxmj  -  7gj9dgxmj 3ƒ 7gj9dgxmjp 诣` File "/opt/conda/lib/python3.12/site-packages/torch/optim/optimizer.py", line 549, in wrapper )  7gj9dgxmj ^& 7gj9dgxmj  "ng= 7gj9dgxmj+ Іout = func(*args, **kwargs) v# 7gj9dgxmj  8+  7gj9dgxmj uU# 7gj9dgxmj  #]B# 7gj9dgxmj  # 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7gj9dgxmj  i9g# 7gj9dgxmj  ᠄# 7gj9dgxmj  a^# 7gj9dgxmj  £# 7gj9dgxmj Ђ }n# 7gj9dgxmj  # 7gj9dgxmj  :l# 7gj9dgxmj  [mKO# 7gj9dgxmj ൂ 2(# 7gj9dgxmj ք^J# 7gj9dgxmj ^?:# 7gj9dgxmj ^Rd# 7gj9dgxmj ^?#&# 7gj9dgxmj ^ s# 7gj9dgxmj к^S# 7gj9dgxmj ^\8j# 7gj9dgxmj Ы^K# 7gj9dgxmj ^.MH# 7gj9dgxmj  '  7gj9dgxmj Ő% 7gj9dgxmj z File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 146, in __call__ N  7gj9dgxmj l& 7gj9dgxmj  YfN 7gj9dgxmj< ,self._result = self.closure(*args, **kwargs)xj=# 7gj9dgxmj  FH  7gj9dgxmj v# 7gj9dgxmj Ȣ qV)# 7gj9dgxmj 謏 _i# 7gj9dgxmj 藖 B# 7gj9dgxmj  ؗi# 7gj9dgxmj ؜ QT# 7gj9dgxmj  =S# 7gj9dgxmj  B'# 7gj9dgxmj  1 # 7gj9dgxmj  21# 7gj9dgxmj ȕ ;N# 7gj9dgxmj  # 7gj9dgxmj  @Ny# 7gj9dgxmj  u# 7gj9dgxmj  ^# 7gj9dgxmj  # 7gj9dgxmj  bx# 7gj9dgxmj  ؓ # 7gj9dgxmj  # 7gj9dgxmj ؤ  # 7gj9dgxmj ^ɞjf# 7gj9dgxmj ^D1# 7gj9dgxmj ^z# 7gj9dgxmj ^-Y# 7gj9dgxmj ^ȣ# 7gj9dgxmj ^^# 7gj9dgxmj ^ٛ# 7gj9dgxmj ^ڋn# 7gj9dgxmj ȑ^Β# 7gj9dgxmj ^T2'# 7gj9dgxmj ^ # 7gj9dgxmj ^*# 7gj9dgxmj ^4# 7gj9dgxmj ^ɒ# 7gj9dgxmj ^`# 7gj9dgxmj ^Ϫ# 7gj9dgxmj ^ca# 7gj9dgxmj ^ # 7gj9dgxmj ^# 7gj9dgxmj ^%s# 7gj9dgxmj ^|# 7gj9dgxmj ^f"0# 7gj9dgxmj ^0ܼ# 7gj9dgxmj ^# 7gj9dgxmj ۔^?C# 7gj9dgxmj Г^ # 7gj9dgxmj ̙^G)V# 7gj9dgxmj ^d# 7gj9dgxmj ^t# 7gj9dgxmj ؈ u_  7gj9dgxmj ރg 7gj9dgxmj{ k File "/opt/conda/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context p08  7gj9dgxmj & 7gj9dgxmj  q> 7gj9dgxmj, return func(*args, **kwargs)# 7gj9dgxmj  <_Mc  7gj9dgxmj ## 7gj9dgxmj ȑ '(# 7gj9dgxmj  IF# 7gj9dgxmj  'I# 7gj9dgxmj  H# 7gj9dgxmj  z4# 7gj9dgxmj  ح2# 7gj9dgxmj  =_n# 7gj9dgxmj ئ +1# 7gj9dgxmj  u # 7gj9dgxmj  ߐ# 7gj9dgxmj  # 7gj9dgxmj ^Bn# 7gj9dgxmj ^# 7gj9dgxmj ^u# 7gj9dgxmj ^# 7gj9dgxmj ^# 7gj9dgxmj ^Kq5# 7gj9dgxmj Ї^h# 7gj9dgxmj ȁ^fr# 7gj9dgxmj ^l0# 7gj9dgxmj ^OY# 7gj9dgxmj ^u*w# 7gj9dgxmj ^# 7gj9dgxmj ^P# 7gj9dgxmj ^sA# 7gj9dgxmj ^ڭpt# 7gj9dgxmj ^_# 7gj9dgxmj Ȥ^Y# 7gj9dgxmj ^&# 7gj9dgxmj ^4# 7gj9dgxmj ^2&e# 7gj9dgxmj ^F# 7gj9dgxmj  _  7gj9dgxmj "B5 7gj9dgxmj y File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 131, in closure s*  7gj9dgxmj 5& 7gj9dgxmj  n? 7gj9dgxmj- ؆step_output = self._step_fn()_# 7gj9dgxmj  WP  7gj9dgxmj # 7gj9dgxmj  +m# 7gj9dgxmj е "֑# 7gj9dgxmj  uѢ# 7gj9dgxmj  %\N# 7gj9dgxmj  n1# 7gj9dgxmj  +Lϧ# 7gj9dgxmj  w# 7gj9dgxmj  U2<# 7gj9dgxmj 蠇^# 7gj9dgxmj ^c# 7gj9dgxmj ^M# 7gj9dgxmj ^850`# 7gj9dgxmj ^v%# 7gj9dgxmj ^fC# 7gj9dgxmj ^P w# 7gj9dgxmj ^^# 7gj9dgxmj ^2^# 7gj9dgxmj Ȍ^j# 7gj9dgxmj ^RIY# 7gj9dgxmj ^7F_# 7gj9dgxmj ^Yyv# 7gj9dgxmj ^'p# 7gj9dgxmj ^qO# 7gj9dgxmj  y  7gj9dgxmj .E 7gj9dgxmj  File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 319, in _training_step %ߋz  7gj9dgxmj q & 7gj9dgxmj  N-_} 7gj9dgxmjk Њ[training_step_output = call._call_strategy_hook(trainer, "training_step", *kwargs.values())7# 7gj9dgxmj  "  7gj9dgxmj ӟJ# 7gj9dgxmj  N# 7gj9dgxmj  }RX# 7gj9dgxmj  \# 7gj9dgxmj  Zr# 7gj9dgxmj Е :v# 7gj9dgxmj Ƴ ePk{# 7gj9dgxmj  IaF# 7gj9dgxmj ا # 7gj9dgxmj  # 7gj9dgxmj  Q# 7gj9dgxmj  Ou# 7gj9dgxmj  x]# 7gj9dgxmj  X# 7gj9dgxmj  # C{# 7gj9dgxmj  # 7gj9dgxmj  # 7gj9dgxmj Ȕ %7# 7gj9dgxmj е l# 7gj9dgxmj  ]J# 7gj9dgxmj  J|# 7gj9dgxmj  L# 7gj9dgxmj  R# 7gj9dgxmj  (U# 7gj9dgxmj ز Kd# 7gj9dgxmj  †# 7gj9dgxmj  M# 7gj9dgxmj  =E5# 7gj9dgxmj ^S # 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7gj9dgxmj ڵ 3o# 7gj9dgxmj  ϤS7# 7gj9dgxmj Ȏ ># 7gj9dgxmj  vm# 7gj9dgxmj  e# 7gj9dgxmj  `# 7gj9dgxmj  .B# 7gj9dgxmj  J# 7gj9dgxmj  Pcmi# 7gj9dgxmj  S# 7gj9dgxmj  ># 7gj9dgxmj  \# 7gj9dgxmj ^0# 7gj9dgxmj ^',# 7gj9dgxmj ^+'# 7gj9dgxmj ^D# 7gj9dgxmj ^ۼ# 7gj9dgxmj Ю^# 7gj9dgxmj ^gk# 7gj9dgxmj П^%# 7gj9dgxmj ^# 7gj9dgxmj ^{# 7gj9dgxmj ^_# 7gj9dgxmj ^I# 7gj9dgxmj ^+# 7gj9dgxmj ^E# 7gj9dgxmj ^GH# 7gj9dgxmj ^0# 7gj9dgxmj ^UR;# 7gj9dgxmj ^}# 7gj9dgxmj ߙ^%# 7gj9dgxmj  J-+  7gj9dgxmj & 7gj9dgxmj v File "/opt/conda/lib/python3.12/site-packages/pytorch_lightning/strategies/strategy.py", line 391, in training_step f0~  7gj9dgxmj Ղx& 7gj9dgxmj  Md] 7gj9dgxmjK ɓ;return self.lightning_module.training_step(*args, **kwargs)#7# 7gj9dgxmj מ H  7gj9dgxmj ɭ91 # 7gj9dgxmj ű 3zS9# 7gj9dgxmj Ĵ # 7gj9dgxmj  uV# 7gj9dgxmj Ț `c # 7gj9dgxmj  fr# 7gj9dgxmj  7@# 7gj9dgxmj  M7c# 7gj9dgxmj  u# 7gj9dgxmj  # 7gj9dgxmj  \r# 7gj9dgxmj  @F# 7gj9dgxmj ^gΘ# 7gj9dgxmj ^hq# 7gj9dgxmj ^ߗ# 7gj9dgxmj ^# 7gj9dgxmj ^ v# 7gj9dgxmj ^d# 7gj9dgxmj ^,̰# 7gj9dgxmj ^"t# 7gj9dgxmj Ȑ^# 7gj9dgxmj ^xS # 7gj9dgxmj ^z$P# 7gj9dgxmj ^qj# 7gj9dgxmj ^# 7gj9dgxmj ^#/# 7gj9dgxmj ^# 7gj9dgxmj ^s$# 7gj9dgxmj ^Tl# 7gj9dgxmj ^ǘ# 7gj9dgxmj ^V}# 7gj9dgxmj ^!| )# 7gj9dgxmj ^Jf# 7gj9dgxmj ȡ^1K# 7gj9dgxmj ڍ^Il# 7gj9dgxmj Ȓ^NzC# 7gj9dgxmj ^{# 7gj9dgxmj ^Ռ# 7gj9dgxmj ^m# 7gj9dgxmj ^hTX# 7gj9dgxmj ^V[D# 7gj9dgxmj ̡^K# 7gj9dgxmj ^T[Zh# 7gj9dgxmj ^Թc# 7gj9dgxmj ^H# 7gj9dgxmj ݫ^b# 7gj9dgxmj ^# 7gj9dgxmj ऱ^(# 7gj9dgxmj ^Yj# 7gj9dgxmj ^Se# 7gj9dgxmj Ȕ^*# 7gj9dgxmj Ի^$i# 7gj9dgxmj Ӿ^A# 7gj9dgxmj ^# 7gj9dgxmj ^ ˯# 7gj9dgxmj ^F.# 7gj9dgxmj ^iG# 7gj9dgxmj ^f# 7gj9dgxmj ؗ^Z!# 7gj9dgxmj ^cYa# 7gj9dgxmj ^=Bbh# 7gj9dgxmj ؗ^# 7gj9dgxmj ^{'# 7gj9dgxmj ^Y# 7gj9dgxmj  w@  7gj9dgxmj 0Uä 7gj9dgxmj  File "/opt/conda/lib/python3.12/site-packages/spanet/network/jet_reconstruction/jet_reconstruction_training.py", line 214, in training_step G\  7gj9dgxmj pY& 7gj9dgxmj  )][G 7gj9dgxmj5 %outputs = self.forward(batch.sources) v# 7gj9dgxmj  u  7gj9dgxmj # 7gj9dgxmj  OŦS# 7gj9dgxmj  3 T# 7gj9dgxmj  # 7gj9dgxmj  ,U# 7gj9dgxmj  u# 7gj9dgxmj ȟ Ј5# 7gj9dgxmj  )u# 7gj9dgxmj  sxN# 7gj9dgxmj  C# 7gj9dgxmj Ш F7# 7gj9dgxmj  X1n# 7gj9dgxmj Й *+k# 7gj9dgxmj  w# 7gj9dgxmj  D# 7gj9dgxmj ث^V^# 7gj9dgxmj ^-q# 7gj9dgxmj ^¡_# 7gj9dgxmj ^?# 7gj9dgxmj ^gS# 7gj9dgxmj ^n;# 7gj9dgxmj ^։k# 7gj9dgxmj ^C3]# 7gj9dgxmj ^l3@# 7gj9dgxmj ޅ^̂# 7gj9dgxmj ^``I# 7gj9dgxmj ߊ^aN # 7gj9dgxmj ^@D# 7gj9dgxmj ^# 7gj9dgxmj ^Ė7# 7gj9dgxmj ^1oI# 7gj9dgxmj ^fW# 7gj9dgxmj ^Q|# 7gj9dgxmj ^c# 7gj9dgxmj ѡ^L\# 7gj9dgxmj ^z# 7gj9dgxmj ʦ^w@# 7gj9dgxmj ^,$# 7gj9dgxmj ^T (# 7gj9dgxmj ^vW# 7gj9dgxmj ^il# 7gj9dgxmj Բ^~# 7gj9dgxmj ˵ 1  7gj9dgxmj [ 7gj9dgxmj  File "/opt/conda/lib/python3.12/site-packages/spanet/network/jet_reconstruction/jet_reconstruction_network.py", line 148, in forward tS  7gj9dgxmj a& 7gj9dgxmj  # 7gj9dgxmj ^!0# 7gj9dgxmj ع^*[]# 7gj9dgxmj ^X# 7gj9dgxmj ^# 7gj9dgxmj Õ^5# 7gj9dgxmj ^ i# 7gj9dgxmj ^oFm# 7gj9dgxmj ^&;G# 7gj9dgxmj מ^J# 7gj9dgxmj ^6(# 7gj9dgxmj ^2S# 7gj9dgxmj ʥ^# 7gj9dgxmj ^I# 7gj9dgxmj ^b5# 7gj9dgxmj 譬^&# 7gj9dgxmj ֮^l# 7gj9dgxmj ^ B# 7gj9dgxmj ^d# 7gj9dgxmj ɵ^ﳉ# 7gj9dgxmj ֻ^[# 7gj9dgxmj ^))# 7gj9dgxmj ^ٛ# 7gj9dgxmj ^@X# 7gj9dgxmj ^$)# 7gj9dgxmj ^RY# 7gj9dgxmj ^3# 7gj9dgxmj ^t<# 7gj9dgxmj ^j CP# 7gj9dgxmj ^cN# 7gj9dgxmj ^$# 7gj9dgxmj ^up2# 7gj9dgxmj ^y# 7gj9dgxmj ^Z# 7gj9dgxmj ^g~# 7gj9dgxmj ^G)# 7gj9dgxmj ^f# 7gj9dgxmj Њ^[!# 7gj9dgxmj ^# 7gj9dgxmj ^fb# 7gj9dgxmj ^# 7gj9dgxmj ^`Kr# 7gj9dgxmj ^# 7gj9dgxmj ؇^!:# 7gj9dgxmj ^)M# 7gj9dgxmj ^;# 7gj9dgxmj ^~U# 7gj9dgxmj ^A# 7gj9dgxmj ^7 # 7gj9dgxmj ^1# 7gj9dgxmj ^pѵ# 7gj9dgxmj ^n# 7gj9dgxmj ӂ^|# 7gj9dgxmj ȋ γ  7gj9dgxmj 2 7gj9dgxmj~ ԡn File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl ]  7gj9dgxmj wd& 7gj9dgxmj  %", 7gj9dgxmj7 'return selܫf._call_impl(*args, **kwargs)wpw<# 7gj9dgxmj  (  7gj9dgxmj Me# 7gj9dgxmj  }# 7gj9dgxmj  &w# 7gj9dgxmj ȵ ld# 7gj9dgxmj Ȭ ## 7gj9dgxmj  # 7gj9dgxmj  3# 7gj9dgxmj  lb# 7gj9dgxmj 譣 :gn# 7gj9dgxmj 褦 # 7gj9dgxmj  .@`# 7gj9dgxmj  Y# 7gj9dgxmj ^H# 7gj9dgxmj ^-@# 7gj9dgxmj ^# 7gj9dgxmj ئ^8# 7gj9dgxmj ^># 7gj9dgxmj ^~# 7gj9dgxmj ؼ^## 7gj9dgxmj ௿^^# 7gj9dgxmj ^ # 7gj9dgxmj ^R# 7gj9dgxmj ^8# 7gj9dgxmj ^Y# 7gj9dgxmj ^# 7gj9dgxmj ^i# 7gj9dgxmj ^Ɵ# 7gj9dgxmj ^bEF# 7gj9dgxmj ^#sl# 7gj9dgxmj Ї^_ # 7gj9dgxmj ^:[# 7gj9dgxmj ^J)# 7gj9dgxmj ^'# 7gj9dgxmj ȿ^#_# 7gj9dgxmj ^Ԋ^# 7gj9dgxmj ^ # 7gj9dgxmj ^Reo# 7gj9dgxmj ^ )# 7gj9dgxmj ^کE# 7gj9dgxmj ^I# 7gj9dgxmj ^U# 7gj9dgxmj ^h# 7gj9dgxmj ^vE# 7gj9dgxmj ^=h# 7gj9dgxmj  u  7gj9dgxmj r 7gj9dgxmjv f File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl y  7gj9dgxmj иVCI& 7gj9dgxmj 艩 KxF 7gj9dgxmj4 $return forward_call(*args, **kwargs)j# 7gj9dgxmj ݼ n:  7gj9dgxmj ‰4# 7gj9dgxmj  w# 7gj9dgxmj  8I# 7gj9dgxmj  L# 7gj9dgxmj  Q"# 7gj9dgxmj  "%# 7gj9dgxmj  W# 7gj9dgxmj  jP# 7gj9dgxmj ܈ vu;G# 7gj9dgxmj  -I# 7gj9dgxmj  F# 7gj9dgxmj ş 'L# 7gj9dgxmj ^# 7gj9dgxmj ^\# 7gj9dgxmj ^^# 7gj9dgxmj ^]# 7gj9dgxmj ^"D4# 7gj9dgxmj ^-# 7gj9dgxmj ^TW# 7gj9dgxmj ^^# 7gj9dgxmj ^,՛# 7gj9dgxmj ^^O# 7gj9dgxmj ^;&# 7gj9dgxmj ^# 7gj9dgxmj ^g/# 7gj9dgxmj ^p_# 7gj9dgxmj ^i# 7gj9dgxmj ^uYQ# 7gj9dgxmj ^# 7gj9dgxmj ^b# 7gj9dgxmj ^FM# 7gj9dgxmj ^l# 7gj9dgxmj ^# 7gj9dgxmj ^GW# 7gj9dgxmj ^# 7gj9dgxmj ܅^ .# 7gj9dgxmj ^XtD# 7gj9dgxmj ^f# 7gj9dgxmj ࡎ^wo# 7gj9dgxmj ^?# 7gj9dgxmj ^<# 7gj9dgxmj  y8  7gj9dgxmj 1Ǒ 7gj9dgxmj o File "/opt/conda/lib/python3.12/site-packages/spanet/network/layers/branch_decoder.py", line 128, in forward r  7gj9dgxmj 3& 7gj9dgxmj  L 7gj9dgxmjn ^encoded_vectors, particle_vector, _ = self.encoder(event_vectors, padding_mask, sequence_mask)c# 7gj9dgxmj  b  7gj9dgxmj Ц)ƛ# 7gj9dgxmj  OY# 7gj9dgxmj ݞ  m# 7gj9dgxmj  W# 7gj9dgxmj  # 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7gj9dgxmj ĵ^g# 7gj9dgxmj ^ ;# 7gj9dgxmj Т^,{# 7gj9dgxmj ۽^p# 7gj9dgxmj Г^yj# 7gj9dgxmj ^hPO8# 7gj9dgxmj ^U4O# 7gj9dgxmj ^b# 7gj9dgxmj ^# 7gj9dgxmj ^W# 7gj9dgxmj ^S3)# 7gj9dgxmj ^?O# 7gj9dgxmj ^!# 7gj9dgxmj ^J*Z# 7gj9dgxmj ^N^# 7gj9dgxmj ^B̻C# 7gj9dgxmj ^A# 7gj9dgxmj ^(u# 7gj9dgxmj Ӌ ݺ  7gj9dgxmj U0 7gj9dgxmj~ n File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl 3  7gj9dgxmj ЇiW& 7gj9dgxmj  8cI 7gj9dgxmj7 'return self._call_impl(*args, **kwargs)c # 7gj9dgxmj  Xf  7gj9dgxmj z# 7gj9dgxmj  # 7gj9dgxmj  q# 7gj9dgxmj  ?K# 7gj9dgxmj  g# 7gj9dgxmj ^"r# 7gj9dgxmj ӱ^ # 7gj9dgxmj ^Л# 7gj9dgxmj 㶁^# 7gj9dgxmj ⹁^ # 7gj9dgxmj 𚼁^# 7gj9dgxmj Ӿ^lY# 7gj9dgxmj ^lO# 7gj9dgxmj Á^}# 7gj9dgxmj ؄Ɓ^.$# 7gj9dgxmj ȁ^uw# 7gj9dgxmj ˁ^sl~# 7gj9dgxmj ΁^{# 7gj9dgxmj с^e# 7gj9dgxmj ԁ^# 7gj9dgxmj ܁^<,f# 7gj9dgxmj ^d|Hs# 7gj9dgxmj ^?# 7gj9dgxmj ^^ # 7gj9dgxmj ^<*# 7gj9dgxmj ^9# 7gj9dgxmj ^+# 7gj9dgxmj ^v# 7gj9dgxmj ^|# 7gj9dgxmj ʧ   7gj9dgxmj ܶ?J 7gj9dgxmj o File "/opt/conda/lib/python3.12/site-packages/spanet/network/layers/stacked_encoder.py", line 81, in forward =  7gj9dgxmj އYm& 7gj9dgxmj  [̒ 7gj9dgxmj rcombined_vectors, gate_logits_list = self.encoder(combined_vectors, combined_padding_mask, combined_sequence_mask)?,6# 7gj9dgxmj  N}  7gj9dgxmj 2hs# 7gj9dgxmj   # 7gj9dgxmj  `# 7gj9dgxmj  ,># 7gj9dgxmj  j~# 7gj9dgxmj  (-# 7gj9dgxmj ɴ Koe# 7gj9dgxmj  ߱|# 7gj9dgxmj ҹ g# 7gj9dgxmj  q9# 7gj9dgxmj þ ,ߒ# 7gj9dgxmj  C# 7gj9dgxmj È iuַ# 7gj9dgxmj ň hS# 7gj9dgxmj ЕȈ Z1# 7gj9dgxmj ʈ X# 7gj9dgxmj ̈ # 7gj9dgxmj اψ jo# 7gj9dgxmj ш Qr # 7gj9dgxmj Ԉ cm!/# 7gj9dgxmj ׈ V9# 7gj9dgxmj ȸو H# 7gj9dgxmj ۈ #ܥ# 7gj9dgxmj ވ Y# 7gj9dgxmj  'Ɣ# 7gj9dgxmj  v^## 7gj9dgxmj  ۾m# 7gj9dgxmj  %ܟ# 7gj9dgxmj  k# 7gj9dgxmj  k# 7gj9dgxmj  _"# 7gj9dgxmj  %o-# 7gj9dgxmj  {.# 7gj9dgxmj  a-# 7gj9dgxmj  ĉ# 7gj9dgxmj  # 7gj9dgxmj 䁉 ,zҸ# 7gj9dgxmj  ,# 7gj9dgxmj Ȯ ҪS# 7gj9dgxmj 爉 0:# 7gj9dgxmj  601# 7gj9dgxmj ȍ M# 7gj9dgxmj ^bέ# 7gj9dgxmj ^%l 6# 7gj9dgxmj ^0# 7gj9dgxmj Т^d7# 7gj9dgxmj ۙ^# 7gj9dgxmj 苜^g{# 7gj9dgxmj ^# 7gj9dgxmj ݠ^!P!# 7gj9dgxmj ^# 7gj9dgxmj ֥^_Ld# 7gj9dgxmj ཨ^i~# 7gj9dgxmj ^eu9# 7gj9dgxmj խ^# 7gj9dgxmj ^|# 7gj9dgxmj 䵉^S # 7gj9dgxmj ^# 7gj9dgxmj κ^߸# 7gj9dgxmj ^# 7gj9dgxmj ^C# 7gj9dgxmj ^Tu# 7gj9dgxmj ĉ^s# 7gj9dgxmj Ɖ^'# 7gj9dgxmj ذɉ^1^B# 7gj9dgxmj ˉ^# 7gj9dgxmj Ή^Gr\# 7gj9dgxmj Љ^O# 7gj9dgxmj ؒӉ^E# 7gj9dgxmj ȻՉ^A# 7gj9dgxmj ׉^/T# 7gj9dgxmj ډ^;# 7gj9dgxmj ܉^7# 7gj9dgxmj ȝ߉^|# 7gj9dgxmj ^13# 7gj9dgxmj ^ƄD# 7gj9dgxmj ^||nC# 7gj9dgxmj ^S 5# 7gj9dgxmj ^cBk# 7gj9dgxmj ^I# 7gj9dgxmj ݀^;o# 7gj9dgxmj ؇^vUH# 7gj9dgxmj ڎ^Vc# 7gj9dgxmj ͕^Y# 7gj9dgxmj ^V"# 7gj9dgxmj ^1̫# 7gj9dgxmj ࢫ^V# 7gj9dgxmj ^# 7gj9dgxmj ^Rv# 7gj9dgxmj 豳^o# 7gj9dgxmj ҵ^} # 7gj9dgxmj ^# 7gj9dgxmj ^r# 7gj9dgxmj ͼ^# 7gj9dgxmj ^k9# 7gj9dgxmj ^W# 7gj9dgxmj Ë^c# 7gj9dgxmj ŋ^`G# 7gj9dgxmj ȋ^# 7gj9dgxmj ʋ^("# 7gj9dgxmj ̋^*t# 7gj9dgxmj ΋^,# 7gj9dgxmj ы^rI-# 7gj9dgxmj Ӌ^pU# 7gj9dgxmj Ջ^@*# 7gj9dgxmj ׋^A# 7gj9dgxmj ڋ^}^# 7gj9dgxmj ȑ݋^Eu # 7gj9dgxmj ߋ^f# 7gj9dgxmj ^ɹ_~# 7gj9dgxmj ^# 7gj9dgxmj ^ ,̣# 7gj9dgxmj ^[:# 7gj9dgxmj ^ }# 7gj9dgxmj ^pr# 7gj9dgxmj ^@# 7gj9dgxmj ^Zu# 7gj9dgxmj ^{)a# 7gj9dgxmj ^XJ# 7gj9dgxmj  (  7gj9dgxmj 𺺌FsÐ 7gj9dgxmj~ Čn File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl Y_  7gj9dgxmj 2& 7gj9dgxmj  I 7gj9dgxmj7 'return self._call_impl(*args, **kwargs)KH# 7gj9dgxmj  Ĕi3  7gj9dgxmj `&# 7gj9dgxmj 㒍 *# 7gj9dgxmj  x# 7gj9dgxmj  <=6# 7gj9dgxmj  f8# 7gj9dgxmj  v;# 7gj9dgxmj  "# 7gj9dgxmj ૢ 6 # 7gj9dgxmj  # 7gj9dgxmj  >-# 7gj9dgxmj  7# 7gj9dgxmj 贬 &?# 7gj9dgxmj ^ # 7gj9dgxmj ^# 7gj9dgxmj Ƴ^˅# 7gj9dgxmj ^Vܷ# 7gj9dgxmj ^=W# 7gj9dgxmj ض^7# 7gj9dgxmj 罍^o # 7gj9dgxmj ^"# 7gj9dgxmj ^QG0# 7gj9dgxmj ō^Wn# 7gj9dgxmj ɍ^;}e# 7gj9dgxmj ̍^EN# 7gj9dgxmj Ѝ^͒=# 7gj9dgxmj Ӎ^ZR# 7gj9dgxmj ׍^# 7gj9dgxmj ڍ^/# 7gj9dgxmj ݍ^nh# 7gj9dgxmj ^^p# 7gj9dgxmj ^;K# 7gj9dgxmj ^cp# 7gj9dgxmj ^SG# 7gj9dgxmj ^\# 7gj9dgxmj ^Ⱥ# 7gj9dgxmj ^1)Q# 7gj9dgxmj ^φj# 7gj9dgxmj ^(;# 7gj9dgxmj ^Iz:!# 7gj9dgxmj ^%6G# 7gj9dgxmj ^k# 7gj9dgxmj ^ X# 7gj9dgxmj ^u# 7gj9dgxmj ^5# 7gj9dgxmj ׎ 8  7gj9dgxmj ZΈ 7gj9dgxmjv f File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl '  7gj9dgxmj a&& 7gj9dgxmj བ HF 7gj9dgxmj4 $return forward_call(*args, **kwargs)# 7gj9dgxmj  j  7gj9dgxmj +b/o# 7gj9dgxmj  H!d# 7gj9dgxmj Ǐ @\# 7gj9dgxmj я D# 7gj9dgxmj ۏ C# 7gj9dgxmj ޏ _# 7gj9dgxmj  'BL# 7gj9dgxmj ئ L]# 7gj9dgxmj  SD-|# 7gj9dgxmj  oֹ(# 7gj9dgxmj  %{# 7gj9dgxmj  # 7gj9dgxmj ^{-# 7gj9dgxmj ^82SJ# 7gj9dgxmj ^čn# 7gj9dgxmj ^f,# 7gj9dgxmj ^ # 7gj9dgxmj Ы^ O # 7gj9dgxmj ɂ^B# 7gj9dgxmj ߅^V!# 7gj9dgxmj ވ^o # 7gj9dgxmj ͋^hx1# 7gj9dgxmj ^c# 7gj9dgxmj ^6v# 7gj9dgxmj ^|# 7gj9dgxmj ^/u(# 7gj9dgxmj ^7# 7gj9dgxmj ^BC# 7gj9dgxmj ^W# 7gj9dgxmj ^+rz# 7gj9dgxmj ^0Z# 7gj9dgxmj ^3# 7gj9dgxmj 蜫^ t# 7gj9dgxmj ݭ^Wa# 7gj9dgxmj 荰^d># 7gj9dgxmj ^??"# 7gj9dgxmj ﴐ^8G# 7gj9dgxmj ا^# 7gj9dgxmj й^G# 7gj9dgxmj ^=$# 7gj9dgxmj ^# 7gj9dgxmj  y  7gj9dgxmj Őr 7gj9dgxmj ȣȐ} File "/opt/conda/lib/python3.12/site-packages/spanet/network/layers/transformer/gated_transformer.py", line 74, in forward ].  7gj9dgxmj Pl{& 7gj9dgxmj  ㏑|X 7gj9dgxmjF Ȯ6output, _ = layer(output, padding_mask, sequence_mask)/(# 7gj9dgxmj ͑   7gj9dgxmj Ց# 7gj9dgxmj ؑ 7 # 7gj9dgxmj ۑ '# 7gj9dgxmj ޑ ™z# 7gj9dgxmj  D&/# 7gj9dgxmj  # 7gj9dgxmj  J# 7gj9dgxmj  1# 7gj9dgxmj  m# 7gj9dgxmj  A?F# 7gj9dgxmj  Qz# 7gj9dgxmj  i# 7gj9dgxmj ȇ # 7gj9dgxmj  ճ^# 7gj9dgxmj  R{|# 7gj9dgxmj  # 7gj9dgxmj  6f# 7gj9dgxmj Є^N":k# 7gj9dgxmj Ё^VH# 7gj9dgxmj ^# 7gj9dgxmj ㋒^E.# 7gj9dgxmj ^ uc# 7gj9dgxmj ^Hv+# 7gj9dgxmj Ւ^V# 7gj9dgxmj ^w# 7gj9dgxmj ^Օ# 7gj9dgxmj 癒^@# 7gj9dgxmj Ɵ^Ɋu# 7gj9dgxmj 襢^Yr(# 7gj9dgxmj ^s*# 7gj9dgxmj ^CVg# 7gj9dgxmj ꭒ^nc# 7gj9dgxmj ^F# 7gj9dgxmj ^Nk# 7gj9dgxmj ^4# 7gj9dgxmj ƹ^B# 7gj9dgxmj ^'# 7gj9dgxmj ৾^R{# 7gj9dgxmj ^ᚣ# 7gj9dgxmj Ò^# 7gj9dgxmj ƒ^l# 7gj9dgxmj Ȓ^e:03# 7gj9dgxmj ˒^# 7gj9dgxmj ͒^Cz# 7gj9dgxmj В^# 7gj9dgxmj Ӓ^ы# 7gj9dgxmj Ւ^B# 7gj9dgxmj ؒ^ # 7gj9dgxmj ے^j# 7gj9dgxmj ޒ^PV# 7gj9dgxmj ^(X# 7gj9dgxmj ^)t# 7gj9dgxmj ^ @h# 7gj9dgxmj ȫ^W# 7gj9dgxmj ^:f# 7gj9dgxmj ؓ^*V^5# 7gj9dgxmj ؝ۓ^q# 7gj9dgxmj ؔޓ^.Vu# 7gj9dgxmj ^Yn# 7gj9dgxmj ȱ  7gj9dgxmj + 7gj9dgxmj~ n File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl 'Bz  7gj9dgxmj ބ0X.& 7gj9dgxmj  b/I 7gj9dgxmj7 Ԋ'return self._call_impl(*args, **kwargs)2# 7gj9dgxmj Í +}  7gj9dgxmj k# 7gj9dgxmj ݔ бO# 7gj9dgxmj ȕ Z\# 7gj9dgxmj Ι ;5# 7gj9dgxmj  u# 7gj9dgxmj  ZW# 7gj9dgxmj ࠔ }݆# 7gj9dgxmj  # 7gj9dgxmj  ?tc# 7gj9dgxmj Ϩ `Y# 7gj9dgxmj Ѐ T̓# 7gj9dgxmj  GA# 7gj9dgxmj گ^# 7gj9dgxmj ^ y# 7gj9dgxmj ೴^## 7gj9dgxmj ^T# 7gj9dgxmj ह^U# 7gj9dgxmj ^Bz# 7gj9dgxmj ^# 7gj9dgxmj Ô^MFM# 7gj9dgxmj Ɣ^H# 7gj9dgxmj Ȕ^vA# 7gj9dgxmj ʔ^N# 7gj9dgxmj ؾ͔^)# 7gj9dgxmj ϔ^Xp# 7gj9dgxmj Ҕ^7'# 7gj9dgxmj Ԕ^hF# 7gj9dgxmj ֔^C# 7gj9dgxmj ٔ^Ѳ# 7gj9dgxmj ۔^ x[# 7gj9dgxmj ޔ^j!# 7gj9dgxmj ^2# 7gj9dgxmj ^X# 7gj9dgxmj ^r!# 7gj9dgxmj ^\ٞ_# 7gj9dgxmj ^t6# 7gj9dgxmj ^$[# 7gj9dgxmj ^v# 7gj9dgxmj ^+Y S# 7gj9dgxmj ^r# 7gj9dgxmj ^?h6# 7gj9dgxmj ^ޗ# 7gj9dgxmj ^ T## 7gj9dgxmj ^z# 7gj9dgxmj   7gj9dgxmj φyީ 7gj9dgxmjv Ήf File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl *!  7gj9dgxmj el& 7gj9dgxmj  8~F 7gj9dgxmj4 $return forward_call(*args, **kwargs)C|# 7gj9dgxmj  O3  7gj9dgxmj 1ϟ# 7gj9dgxmj   3# 7gj9dgxmj  N{# 7gj9dgxmj  J# 7gj9dgxmj  v# 7gj9dgxmj  PA># 7gj9dgxmj  oi# 7gj9dgxmj  m# 7gj9dgxmj ꮖ G# 7gj9dgxmj  C# 7gj9dgxmj  l# 7gj9dgxmj  |# 7gj9dgxmj Ö^bm# 7gj9dgxmj ɖ^%y# 7gj9dgxmj Ж^{# 7gj9dgxmj ֖^9Sd# 7gj9dgxmj ۖ^}a# 7gj9dgxmj ^tw # 7gj9dgxmj ^R# 7gj9dgxmj п^{0ӎ# 7gj9dgxmj œ^9E# 7gj9dgxmj ^x|M# 7gj9dgxmj 𫞗^+B# 7gj9dgxmj ء^# 7gj9dgxmj ^ # 7gj9dgxmj ί^Z# 7gj9dgxmj ^T}C# 7gj9dgxmj ^x# 7gj9dgxmj ^ة# 7gj9dgxmj Ǘ^ # 7gj9dgxmj ̗^# 7gj9dgxmj ӗ^# 7gj9dgxmj ؗ^F# 7gj9dgxmj ߗ^?# 7gj9dgxmj ^uG# 7gj9dgxmj М^78# 7gj9dgxmj ^ŝ # 7gj9dgxmj Ș^$# 7gj9dgxmj ^Z# 7gj9dgxmj ^o# 7gj9dgxmj 𷗘^D# 7gj9dgxmj Ø k  7gj9dgxmj ɘ6Y 7gj9dgxmj Ҙ} File "/opt/conda/lib/python3.12/site-packages/spanet/network/layers/transformer/gated_transformer.py", line 50, in forward s  7gj9dgxmj & 7gj9dgxmj  2%S 7gj9dgxmjA Պ1output = self.feed_forward(output, sequence_mask)E܉# 7gj9dgxmj  #  7gj9dgxmj ڥHB"# 7gj9dgxmj  ;9# 7gj9dgxmj 趱 ?l# 7gj9dgxmj  # 7gj9dgxmj  t1tw# 7gj9dgxmj ™ u# 7gj9dgxmj Ǚ k# 7gj9dgxmj ˙ U# 7gj9dgxmj ϙ X# 7gj9dgxmj ә *GA# 7gj9dgxmj ٙ rp# 7gj9dgxmj ޙ 53W# 7gj9dgxmj  lN# 7gj9dgxmj  m+$# 7gj9dgxmj ^!# 7gj9dgxmj ^# 7gj9dgxmj ^!# 7gj9dgxmj ^# 7gj9dgxmj ֌^,%# 7gj9dgxmj 鐚^KA# 7gj9dgxmj ^p%o# 7gj9dgxmj ț^Q>m# 7gj9dgxmj ꢚ^(DT# 7gj9dgxmj ^(# 7gj9dgxmj ^Q# 7gj9dgxmj ȋ^S# 7gj9dgxmj ^# 7gj9dgxmj Ծ^("M# 7gj9dgxmj Ú^vF# 7gj9dgxmj ؔɚ^Eo# 7gj9dgxmj ֚^e# 7gj9dgxmj ۚ^?# 7gj9dgxmj ߚ^/7H5# 7gj9dgxmj ^Sƅ# 7gj9dgxmj ^!# 7gj9dgxmj آ^2# 7gj9dgxmj ^# 7gj9dgxmj ^# 7gj9dgxmj ^$rb# 7gj9dgxmj ^軉# 7gj9dgxmj ^# 7gj9dgxmj Ƀ^:K.# 7gj9dgxmj ^# 7gj9dgxmj Ћ^`# 7gj9dgxmj ؐ^ # 7gj9dgxmj ^R# 7gj9dgxmj ^f# 7gj9dgxmj ^m,# 7gj9dgxmj ^w# 7gj9dgxmj ^/# 7gj9dgxmj ^>$~# 7gj9dgxmj ʛ^B)# 7gj9dgxmj Λ^# 7gj9dgxmj ћ^~4# 7gj9dgxmj כ D"  7gj9dgxmj ޛ_ 7gj9dgxmj~ n File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl >  7gj9dgxmj & 7gj9dgxmj  5I 7gj9dgxmj7 'return self._call_impl(*args, **kwargs)u# 7gj9dgxmj  y\  7gj9dgxmj *# 7gj9dgxmj ǭ V}# 7gj9dgxmj 鱜 f# 7gj9dgxmj ݵ @# 7gj9dgxmj ¹ e# 7gj9dgxmj Ɯ ٬ # 7gj9dgxmj ɜ # 7gj9dgxmj ȥ͜ &W# 7gj9dgxmj М )# 7gj9dgxmj Ӝ QE# 7gj9dgxmj ȇל q!$# 7gj9dgxmj Хڜ _?# 7gj9dgxmj ݜ^# 7gj9dgxmj ^N# 7gj9dgxmj ^ # 7gj9dgxmj ^b# 7gj9dgxmj ^# 7gj9dgxmj ^d4n# 7gj9dgxmj ^.jL# 7gj9dgxmj ^v# 7gj9dgxmj ^q# 7gj9dgxmj ^# 7gj9dgxmj ^--# 7gj9dgxmj ^# 7gj9dgxmj ^Ȧ# 7gj9dgxmj ^(2# 7gj9dgxmj 𮋝^d # 7gj9dgxmj 𥎝^L # 7gj9dgxmj ^ x# 7gj9dgxmj ^&# 7gj9dgxmj ^jq# 7gj9dgxmj ؉^;# 7gj9dgxmj ^ؾ:# 7gj9dgxmj ԣ^g# 7gj9dgxmj ˦^/# 7gj9dgxmj ©^# 7gj9dgxmj ^E# 7gj9dgxmj ^ѷ# 7gj9dgxmj ^<# 7gj9dgxmj ^@G# 7gj9dgxmj ^NV# 7gj9dgxmj ^P# 7gj9dgxmj ^j*# 7gj9dgxmj ŝ^eQ# 7gj9dgxmj ̝ w  7gj9dgxmj ϝ&`m 7gj9dgxmjv ӝf File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl K0(  7gj9dgxmj 1w& 7gj9dgxmj  wF 7gj9dgxmj4 ˁ$return forward_call(*args, **kwargs)SK# 7gj9dgxmj 𱇞  7gj9dgxmj )y# 7gj9dgxmj  ؈G# 7gj9dgxmj ▞ K# 7gj9dgxmj  q# 7gj9dgxmj ͝ # 7gj9dgxmj Ġ l"# 7gj9dgxmj  # 7gj9dgxmj  u# 7gj9dgxmj К J;# 7gj9dgxmj  !I=# 7gj9dgxmj  &# 7gj9dgxmj ߹ # 7gj9dgxmj ؔ^# 7gj9dgxmj Ş^;v# 7gj9dgxmj Ȟ^Y# 7gj9dgxmj Ξ^{# 7gj9dgxmj ў^)I# 7gj9dgxmj ֞^_p# 7gj9dgxmj ٞ^P~# 7gj9dgxmj ܞ^&e# 7gj9dgxmj إ^銬# 7gj9dgxmj ^8=F# 7gj9dgxmj ^<# 7gj9dgxmj ^,# 7gj9dgxmj ^ # 7gj9dgxmj ^p # 7gj9dgxmj ^}G# 7gj9dgxmj ^sp# 7gj9dgxmj ݀^# 7gj9dgxmj ^N# 7gj9dgxmj Ԉ^h# 7gj9dgxmj Ë^O5# 7gj9dgxmj ʎ^H# 7gj9dgxmj ^V+# 7gj9dgxmj ^X# 7gj9dgxmj ^AC# 7gj9dgxmj Ȏ^5v # 7gj9dgxmj ȅ^Dh# 7gj9dgxmj ^A # 7gj9dgxmj ٫^8N# 7gj9dgxmj ׮^@# 7gj9dgxmj nj يw  7gj9dgxmj ^ 7gj9dgxmj w File "/opt/conda/lib/python3.12/site-packages/spanet/network/layers/linear_block/gru_block.py", line 118, in forward j6)  7gj9dgxmj  H1~& 7gj9dgxmj Π tM 7gj9dgxmj; Ӡ+output = self.gru(output, self.residual(x))b# 7gj9dgxmj Їؠ Eu  7gj9dgxmj L# 7gj9dgxmj  Pl# 7gj9dgxmj ȡ f# 7gj9dgxmj Ȇ 9~# 7gj9dgxmj  ly# 7gj9dgxmj В ,rbd# 7gj9dgxmj  uU# 7gj9dgxmj  # 7gj9dgxmj 輗 tx# 7gj9dgxmj ߛ (5D# 7gj9dgxmj  c{# 7gj9dgxmj 𿣡 `# 7gj9dgxmj 艨 ЃaG# 7gj9dgxmj Ϋ Cr# 7gj9dgxmj ^EW# 7gj9dgxmj ^;# 7gj9dgxmj ^D# 7gj9dgxmj ^;A# 7gj9dgxmj ^<# 7gj9dgxmj á^{# 7gj9dgxmj ơ^+# 7gj9dgxmj ɡ^*B# 7gj9dgxmj Ρ^_# 7gj9dgxmj ݡ^_^# 7gj9dgxmj ؊^LĆ# 7gj9dgxmj ^aS;v# 7gj9dgxmj ^G# 7gj9dgxmj ^\# 7gj9dgxmj ^k_# 7gj9dgxmj ^Hg# 7gj9dgxmj ^_# 7gj9dgxmj ^ػ# 7gj9dgxmj ^Jn# 7gj9dgxmj ^# 7gj9dgxmj ^ # 7gj9dgxmj ࢢ^5# 7gj9dgxmj د^go# 7gj9dgxmj ū^*/# 7gj9dgxmj ^M n# 7gj9dgxmj ^vV=# 7gj9dgxmj ^y|# 7gj9dgxmj ^}# 7gj9dgxmj ^b# 7gj9dgxmj ^ # 7gj9dgxmj з¢^# 7gj9dgxmj Ƣ^^M# 7gj9dgxmj ɢ^ ݬ# 7gj9dgxmj ΢^ i# 7gj9dgxmj ֢   7gj9dgxmj ڢ+ 7gj9dgxmj~ n File "/opt/conda/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl `s  7gj9dgxmj WF& 7gj9dgxmj  ߠI 7gj9dgxmj7 Д'return self._call_impl(*args, **kwargs)t#c@# 7gj9dgxmj  :  7gj9dgxmj # 7gj9dgxmj ؔ rh# 7gj9dgxmj  [$# 7gj9dgxmj ã @t# 7gj9dgxmj ǣ  :# 7gj9dgxmj ʣ L[# 7gj9dgxmj ͣ 3# 7gj9dgxmj ѣ @># 7gj9dgxmj ԣ =# 7gj9dgxmj ȿ٣ DQ# 7gj9dgxmj ȳݣ %R# 7gj9dgxmj  ~;# 7gj9dgxmj ^Fp6# 7gj9dgxmj ^Ao2# 7gj9dgxmj ^qY;# 7gj9dgxmj ؼ^w`$# 7gj9dgxmj ^0# 7gj9dgxmj 솤^(# 7gj9dgxmj ^)Q# 7gj9dgxmj ^Z# 7gj9dgxmj ^t`# 7gj9dgxmj ^QH# 7gj9dgxmj ^.xv# 7gj9dgxmj ^# 7gj9dgxmj ^t# 7gj9dgxmj ^v# 7gj9dgxmj ߊ^Wĸ(# 7gj9dgxmj Î^3# 7gj9dgxmj ʑ^# 7gj9dgxmj ^;# 7gj9dgxmj 虥^0## 7gj9dgxmj ز^_8# 7gj9dgxmj ^g~# 7gj9dgxmj ؚ^ڐ'# 7gj9dgxmj ^ee# 7gj9dgxmj ؅^a# 7gj9dgxmj DZ^۰B# 7gj9dgxmj 起^{# 7gj9dgxmj Ȋ^oB# 7gj9dgxmj ܿ^lgw# 7gj9dgxmj å^ # 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