performance metrics is zero

Can you please help me with the following things.
I have create a custom dataset with same structure as docred and tried to train the model. First of all it's not seems training by looking at performace metrics.
Also after some epochs it's gives error and stop training. you can check the following logs.
datasets:
  train_path: ./data/datasets/docred_joint/train_joint.json
  valid_path: ./data/datasets/docred_joint/dev_joint.json
  test_path: null
  types_path: ./data/datasets/docred_joint/types.json
model:
  model_type: joint_multi_instance
  encoder_path: bert-base-cased
  tokenizer_path: bert-base-cased
  mention_threshold: 0.85
  coref_threshold: 0.85
  rel_threshold: 0.6
  prop_drop: 0.1
  meta_embedding_size: 25
  size_embeddings_count: 40
  ed_embeddings_count: 300
  token_dist_embeddings_count: 700
  sentence_dist_embeddings_count: 50
  position_embeddings_count: 700
sampling:
  neg_mention_count: 200
  neg_coref_count: 200
  neg_relation_count: 200
  max_span_size: 10
  sampling_processes: 8
  neg_mention_overlap_ratio: 0.5
  lowercase: false
loss:
  mention_weight: 1.0
  coref_weight: 1.0
  entity_weight: 0.25
  relation_weight: 1.0
inference:
  valid_batch_size: 1
  test_batch_size: 1
  max_spans: null
  max_coref_pairs: null
  max_rel_pairs: null
training:
  batch_size: 1
  min_epochs: 20
  max_epochs: 20
  lr: 5.0e-05
  lr_warmup: 0.1
  weight_decay: 0.01
  max_grad_norm: 1.0
  accumulate_grad_batches: 1
  max_spans: null
  max_coref_pairs: null
  max_rel_pairs: null
distribution:
  gpus: []
  accelerator: ''
  prepare_data_per_node: false
misc:
  store_predictions: true
  store_examples: true
  flush_logs_every_n_steps: 1000
  log_every_n_steps: 1000
  deterministic: false
  seed: null
  cache_path: null
  precision: 32
  profiler: null
  final_valid_evaluate: true

Parse dataset '/content/jerex/data/datasets/docred_joint/train_joint.json': 100% 260/260 [00:02<00:00, 111.80it/s]
Parse dataset '/content/jerex/data/datasets/docred_joint/dev_joint.json': 100% 30/30 [00:00<00:00, 120.30it/s]
Some weights of the model checkpoint at bert-base-cased were not used when initializing JointMultiInstanceModel: ['cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.seq_relationship.weight', 'cls.seq_relationship.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.LayerNorm.bias', 'bert.pooler.dense.weight', 'bert.pooler.dense.bias']
- This IS expected if you are initializing JointMultiInstanceModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing JointMultiInstanceModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of JointMultiInstanceModel were not initialized from the model checkpoint at bert-base-cased and are newly initialized: ['mention_localization.linear.weight', 'mention_localization.linear.bias', 'mention_localization.mention_classifier.weight', 'mention_localization.mention_classifier.bias', 'mention_localization.size_embeddings.weight', 'coreference_resolution.coref_linear.weight', 'coreference_resolution.coref_linear.bias', 'coreference_resolution.coref_classifier.weight', 'coreference_resolution.coref_classifier.bias', 'coreference_resolution.coref_ed_embeddings.weight', 'entity_classification.linear.weight', 'entity_classification.linear.bias', 'entity_classification.entity_classifier.weight', 'entity_classification.entity_classifier.bias', 'relation_classification.pair_linear.weight', 'relation_classification.pair_linear.bias', 'relation_classification.rel_linear.weight', 'relation_classification.rel_linear.bias', 'relation_classification.rel_classifier.weight', 'relation_classification.rel_classifier.bias', 'relation_classification.token_distance_embeddings.weight', 'relation_classification.sentence_distance_embeddings.weight', 'relation_classification.entity_type_embeddings.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
GPU available: True, used: False
TPU available: False, using: 0 TPU cores
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/utilities/distributed.py:52: UserWarning: GPU available but not used. Set the --gpus flag when calling the script.
  warnings.warn(*args, **kwargs)

  | Name  | Type                    | Params
--------------------------------------------------
0 | model | JointMultiInstanceModel | 113 M
--------------------------------------------------
113 M     Trainable params
0         Non-trainable params
113 M     Total params
455.678   Total estimated model params size (MB)
Epoch 0:  90% 260/290 [05:11<00:35,  1.20s/it, loss=0.568, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values.
To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at  /pytorch/aten/src/ATen/native/BinaryOps.cpp:467.)
  return torch.floor_divide(self, other)

Epoch 0: 100% 290/290 [05:20<00:00,  1.10s/it, loss=0.568, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.51it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 0: 100% 290/290 [05:24<00:00,  1.12s/it, loss=0.568, v_num=0_0]
                                               tcmalloc: large alloc<PHONE_NUMBER> bytes == 0x56535c070000 @  0x7fa2102d4615 0x56526cb7b4cc 0x56526cc5b47a 0x56526cb81f0c 0x7fa20ae659e4 0x7fa20ae6e0e4 0x7fa20ae42bf0 0x7fa168968935 0x7fa16896426e 0x7fa16896940a 0x7fa20ae4313e 0x7fa20a8d8f98 0x56526cb7f098 0x56526cbf24d9 0x56526cbecced 0x56526cb7fbda 0x56526cbed915 0x56526cbec9ee 0x56526cb7fbda 0x56526cbf1d00 0x56526cb7fafa 0x56526cbed915 0x56526cbec9ee 0x56526cb7fbda 0x56526cbedc0d 0x56526cbec9ee 0x56526cb7fbda 0x56526cbf1d00 0x56526cb7fafa 0x56526cbedc0d 0x56526cb7fafa
tcmalloc: large alloc<PHONE_NUMBER> bytes == 0x5653a962a000 @  0x7fa2102d4615 0x56526cb7b4cc 0x56526cc5b47a 0x56526cb81f0c 0x7fa20ae659e4 0x7fa20ae6e0e4 0x7fa20ae42bf0 0x7fa168968935 0x7fa16896426e 0x7fa16896940a 0x7fa20ae4313e 0x7fa20a8d8f98 0x56526cb7f098 0x56526cbf24d9 0x56526cbecced 0x56526cb7fbda 0x56526cbed915 0x56526cbec9ee 0x56526cb7fbda 0x56526cbf1d00 0x56526cb7fafa 0x56526cbed915 0x56526cbec9ee 0x56526cb7fbda 0x56526cbedc0d 0x56526cbec9ee 0x56526cb7fbda 0x56526cbf1d00 0x56526cb7fafa 0x56526cbedc0d 0x56526cb7fafa
Epoch 1:  90% 260/290 [05:23<00:37,  1.24s/it, loss=0.817, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 1: 100% 290/290 [05:31<00:00,  1.14s/it, loss=0.817, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.49it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 1: 100% 290/290 [05:35<00:00,  1.16s/it, loss=0.817, v_num=0_0]
Epoch 2:  90% 260/290 [05:40<00:39,  1.31s/it, loss=0.343, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 2: 100% 290/290 [05:48<00:00,  1.20s/it, loss=0.343, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.51it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 2: 100% 290/290 [05:52<00:00,  1.22s/it, loss=0.343, v_num=0_0]
Epoch 3:  90% 260/290 [05:49<00:40,  1.34s/it, loss=0.175, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 3: 100% 290/290 [05:57<00:00,  1.23s/it, loss=0.175, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.50it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 3: 100% 290/290 [06:01<00:00,  1.25s/it, loss=0.175, v_num=0_0]
Epoch 4:  90% 260/290 [06:16<00:43,  1.45s/it, loss=0.12, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 4: 100% 290/290 [06:25<00:00,  1.33s/it, loss=0.12, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.39it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 4: 100% 290/290 [06:29<00:00,  1.34s/it, loss=0.12, v_num=0_0]
Epoch 5:  90% 260/290 [06:05<00:42,  1.41s/it, loss=0.117, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 5: 100% 290/290 [06:14<00:00,  1.29s/it, loss=0.117, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.52it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 5: 100% 290/290 [06:17<00:00,  1.30s/it, loss=0.117, v_num=0_0]
Epoch 6:  90% 260/290 [06:07<00:42,  1.41s/it, loss=0.1, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 6: 100% 290/290 [06:16<00:00,  1.30s/it, loss=0.1, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.47it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 6: 100% 290/290 [06:20<00:00,  1.31s/it, loss=0.1, v_num=0_0]
Epoch 7:  90% 260/290 [06:04<00:42,  1.40s/it, loss=0.153, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 7: 100% 290/290 [06:12<00:00,  1.29s/it, loss=0.153, v_num=0_0]
Validating: 100% 30/30 [00:12<00:00,  2.49it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 7: 100% 290/290 [06:16<00:00,  1.30s/it, loss=0.153, v_num=0_0]
Epoch 8:  90% 260/290 [06:11<00:42,  1.43s/it, loss=0.0601, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 8: 100% 290/290 [06:20<00:00,  1.31s/it, loss=0.0601, v_num=0_0]
Validating: 100% 30/30 [00:13<00:00,  2.27it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 8: 100% 290/290 [06:25<00:00,  1.33s/it, loss=0.0601, v_num=0_0]
Epoch 9:  90% 260/290 [06:21<00:44,  1.47s/it, loss=0.0318, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 9: 100% 290/290 [06:30<00:00,  1.35s/it, loss=0.0318, v_num=0_0]
Validating: 100% 30/30 [00:13<00:00,  2.25it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 9: 100% 290/290 [06:35<00:00,  1.36s/it, loss=0.0318, v_num=0_0]
Epoch 10:  90% 260/290 [06:23<00:44,  1.47s/it, loss=0.0143, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Validating:   0% 0/30 [00:00<?, ?it/s]
Epoch 10: 100% 290/290 [06:33<00:00,  1.36s/it, loss=0.0143, v_num=0_0]
Validating: 100% 30/30 [00:14<00:00,  2.15it/s]Evaluation

--- Entity Mentions ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Clusters (Coreference Resolution) ---

                type    precision       recall     f1-score      support
              Binary         0.00         0.00         0.00        111.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Entities ---

                type    precision       recall     f1-score      support
               PRICE         0.00         0.00         0.00          3.0
               ALIAS         0.00         0.00         0.00         40.0
           LIABILITY         0.00         0.00         0.00          2.0
           REFERENCE         0.00         0.00         0.00         34.0
             ADDRESS         0.00         0.00         0.00         32.0

               micro         0.00         0.00         0.00        111.0
               macro         0.00         0.00         0.00        111.0

--- Relations ---
Without entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0

With entity type

                type    precision       recall     f1-score      support
       ALIAS_ADDRESS         0.00         0.00         0.00          7.0
     LIABILITY_PRICE         0.00         0.00         0.00          3.0
     ALIAS_REFERENCE         0.00         0.00         0.00         12.0
   REFERENCE_ADDRESS         0.00         0.00         0.00         10.0

               micro         0.00         0.00         0.00         32.0
               macro         0.00         0.00         0.00         32.0
Epoch 10: 100% 290/290 [06:37<00:00,  1.37s/it, loss=0.0143, v_num=0_0]
Epoch 11:  90% 260/290 [06:21<00:44,  1.47s/it, loss=0.0324, v_num=0_0]
Validating: 0it [00:00, ?it/s]
Epoch 11:  97% 280/290 [06:24<00:13,  1.37s/it, loss=0.0324, v_num=0_0]
Traceback (most recent call last):
  File "./jerex_train.py", line 20, in train
    model.train(cfg)
  File "/content/jerex/jerex/model.py", line 341, in train
    trainer.fit(model, datamodule=data_module)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 499, in fit
    self.dispatch()
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 546, in dispatch
    self.accelerator.start_training(self)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/accelerators/accelerator.py", line 73, in start_training
    self.training_type_plugin.start_training(trainer)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 114, in start_training
    self._results = trainer.run_train()
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 637, in run_train
    self.train_loop.run_training_epoch()
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/training_loop.py", line 577, in run_training_epoch
    self.trainer.run_evaluation(on_epoch=True)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py", line 725, in run_evaluation
    output = self.evaluation_loop.evaluation_step(batch, batch_idx, dataloader_idx)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/evaluation_loop.py", line 166, in evaluation_step
    output = self.trainer.accelerator.validation_step(args)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/accelerators/accelerator.py", line 177, in validation_step
    return self.training_type_plugin.validation_step(*args)
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 131, in validation_step
    return self.lightning_module.validation_step(*args, **kwargs)
  File "/content/jerex/jerex/model.py", line 126, in validation_step
    return self._inference(batch, batch_idx)
  File "/content/jerex/jerex/model.py", line 176, in _inference
    output = self(**batch, inference=True)
  File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/content/jerex/jerex/model.py", line 106, in forward
    max_rel_pairs=max_rel_pairs, inference=inference)
  File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/content/jerex/jerex/models/joint_models.py", line 144, in forward
    return self._forward_inference(*args, **kwargs)
  File "/content/jerex/jerex/models/joint_models.py", line 209, in _forward_inference
    mention_sample_masks, max_spans=max_spans, max_coref_pairs=max_coref_pairs)
  File "/content/jerex/jerex/models/joint_models.py", line 100, in _forward_inference_common
    valid_mentions, self._coref_threshold)
  File "/content/jerex/jerex/models/misc.py", line 135, in create_clusters
    assignments = agg_clustering.fit_predict(distances)
  File "/usr/local/lib/python3.7/dist-packages/sklearn/cluster/_agglomerative.py", line 902, in fit_predict
    return super().fit_predict(X, y)
  File "/usr/local/lib/python3.7/dist-packages/sklearn/base.py", line 462, in fit_predict
    self.fit(X)
  File "/usr/local/lib/python3.7/dist-packages/sklearn/cluster/_agglomerative.py", line 796, in fit
    X = check_array(X, ensure_min_samples=2, estimator=self)
  File "/usr/local/lib/python3.7/dist-packages/sklearn/utils/validation.py", line 586, in check_array
    context))
ValueError: Found array with 1 sample(s) (shape=(1, 1)) while a minimum of 2 is required by AgglomerativeClustering.

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

Hi,
first of all, each entity cluster in your dataset only consists of a single mention. Are you sure JEREX is the right approach here? Maybe a model that extracts relations between single mentions and not clusters of mentions is better suited in this case, like SpERT (https://github.com/lavis-nlp/spert -> self-promotion :) ).
Maybe the code is missing a corner case handling in case there are no (positive) coreference samples. Unfortunately, I won't be able to look at the problem for two weeks since I'm on vacation as of tomorrow.
Does the model train when you only localize entities (by setting model_type in configuration file to 'mention_localization')?
Also, if you want to, you can send me the dataset by email (markus_eberts@yahoo.de). This will certainly help for debugging.

Please leave a comment if your issue is still not resolved.


Add json-item types

Please squash these changes and make a nice commit message.

Looks good to me as well (after the squash :) ).

I merged the squashed version of this change. Please close.


Shorthands are not rendered right when making subscripts

I defined a shorthand:
#show: shorthands.with(
    ($@*$, $times.circle$),
  )

but when I type $@*_C$, it is rendered as

instead of

As an user of this package, I endorse this issue. Correctly managing subscripts is more than an edge case. Suppose in fact you have a content block where a certain command in an equation is repeated very often, and you want to replace that command with a shorter expression that applies only locally. Recently, I had to develop this definition where the underline command is repeated very often:
#definition(name: [Herbrand model])[
    Given an ASP program $Pi$, an interpretation $I subset.eq "HB"(Pi)$ is a _Herbrand model_ of

    - A ground rule $r = H (underline(t)_0) <- P_1 (underline(t)_1), ..., P_n (underline(t)_n).$ of $Pi$ if $ { P_1 (underline(t)_1), ..., P_n (underline(t)_n) } subset.eq I$ implies $H (underline(t)_0) in I$;
    - A rule $r = H (underline(x)_0) <- P_1 (underline(x)_1), ..., P_n (underline(x)_n).$ if $I$ is a Herbrand model of all ground instances of $r$;
    - $Pi$ if $I$ is a Herbrand model of all rules of $Pi$.
]

I tried doing something like the following using shorthands, but I couldn't get it working.
#definition(name: [Herbrand model])[
    #show: shorthands.with(
	($t$, $underline("t")$),
	($x$, $underline("x")$)
    )
    Given an ASP program $Pi$, an interpretation $I subset.eq "HB"(Pi)$ is a _Herbrand model_ of

    - A ground rule $r = H (t_0) <- P_1 (t_1), ..., P_n (t_n).$ of $Pi$ if $ { P_1 (t_1), ..., P_n (t_n) } subset.eq I$ implies $H (t_0) in I$;
    - A rule $r = H (x_0) <- P_1 (x_1), ..., P_n (x_n).$ if $I$ is a Herbrand model of all ground instances of $r$;
    - $Pi$ if $I$ is a Herbrand model of all rules of $Pi$.
]

It goes without saying that correctly handling subscripts in this package would increase its usefulness.

The problem is that the attachment happens before the shorthand is converted, thus when this package tries to apply the shorthands, it sees the content sequence ([@], attach([*], b: [C])), which it currently cannot convert as it doesn't match the given shorthand ([@], [*]). Parsing and replacing this correctly for all math elements is probably going to be a bit of work.
In @acsor's case, you can probably get around it by just using normal show rules, as it doesn't involve multi-character shorthands, which can't currently be matched with regexes:
#definition(...)[
  #show math.equation: it => {
    show regex("^(t|x)$"): math.underline // or maybe regex("\b(t|x)\b")
    it
  }

  Given ...
]

I have added better support for single-element shorthands, and an exception for attachments and fractions, so that you can do things like
#show: shorthands.with(($@*$, $times.circle$))

$ x @*_C y \
  x / @* $

This is still limiting, as you can't have shorthands in attachments like that, but that just doesn't seem possible. Consider the case
#show: shorthands.with($+-$, $plus.minus$)

$ A_+^+- $

which would be detected as the sequence (attach([A], t: [+], b: [+]), [-]). As this representation internally has a fixed argument order, the same sequence would result from $ A^+_+- $, so it would be impossible tell whether the top or bottom attachment should be converted to ±.


[Doc] Update Clerk guide to Next.js app router

https://zenstack.dev/docs/guides/authentication/clerk

@ymc9 I managed to get Clerk working with ZenStack and App Router
Here's what my code looks like in /src/app/api/model/[...path]/route.ts: https://gist.github.com/andrictham/1f4d729f33a63ab1fa817b40418f6e35

It's live here now: https://zenstack.dev/docs/guides/authentication/clerk#create-an-enhanced-prisma-client
The sample project also has two branches for the app router and pages router, respectively.
@andrictham

Fixed in v2.2.0


refactoring: increase bash robustness

Hi,
I have a couple of improvements to increase the robustness of the shell script :-)

Hi @Entepotenz thanks for the PRs! I've added triggers for the CI to run on PRs as well so we can make sure everything still works 🙂 if you rebase your PR it should bring those changes in


Use setContext instead of global store

Unfortunately I see a fundamental design flaw in the way sveltekit-i18n implements the localisation store: If I see it correctly it uses a global store to manage localisation state. On most SSR environments this means localisation state is unintentionally shared between users.
For most smaller applications this doesn't have any visible effect because localisation state is set at the beginning of the request and the request is completed before another user's request is received.
But in high traffic environments and / or slow rendering pages the following could happen:

User A has a locale en. State is set, the page starts rendering with locale en.
While user A's request is still being rendered on the server, User B makes a request with a different locale, say cn. This modifies the global locale state.
User A's request will now finish rendering with locale cn!

The Sveltekit docs explicitly state to avoid global stores for exactly this reason:
https://kit.svelte.dev/docs/state-management
The better way to solve this would be to utilise setContext on the root layout to get a contextualised store. I've tried to do this in my app like this:
// /src/routes/+layout.js
export function load({ url }) {
  return {
    locale: cookies.get('locale') || 'en',
    path: url.pathname,
  };
}

<slot/>

    {$t('home.title')}

This is working fine client-side. But server side no translation happens at all, due to the fact that the line $: i18n.loadTranslations(data.locale, data.path); returns a promise that isn't resolved before Sveltekit returns the rendered page. awaiting that promise before mounting <slot/> just makes SSR return no DOM at all for that slot.
The idiomatic way to await something would be inside the load function instead. But inside the load function I can't access context. I can't load the translations inside the load function and pass the I18n object  as part of data either, because only plain objects are allowed.
Any Idea on how to get out of this pickle? The easiest way would be to make loadTranslations blocking.

I can't load the translations inside the load function and pass the I18n object as part of data either, because only plain objects are allowed.

No. load can return any kind of value. The only load functions that are limited on the type of values it can return are the ones defined in a +server.js file, not the case here.

This worked very well for me:
src/routes/+layout.server.ts:
export function load({ request }) {
  return {
    languages:
      request.headers
        .get("accept-language")
        ?.split(",")
        ?.map(lang => lang.split(";")[0].trim()) ?? [],
  };
}

src/routes/+layout.ts:
import { browser } from "$app/environment";
import { loadTranslations } from "$lib/utils/i18n";

export async function load({ url, data }) {
  const languages = browser ? navigator.languages : data.languages;

  return {
    t: await loadTranslations(languages, url.pathname),
  };
}

src/routes/+layout.svelte:

<slot />

src/app.d.ts:
declare module "svelte" {
  export function getContext(key: "t"): Awaited<ReturnType<typeof import("$lib/utils/i18n")["loadTranslations"]>>;
}

src/lib/utils/i18n.ts:
const config: Config = {
  loaders: [
    // ...
  ]
};

const availableLanguages = new Set(config.loaders?.map(loader => loader.locale) ?? []);
const defaultLocale = "en";
const defaultLocaleForLanguage: Record<string, string> = {
  en: "en-US",
  pt: "pt-BR",
};

export async function loadTranslations(languages: readonly string[], route: string) {
  const locale =
    languages.find(lang =>
      availableLanguages.has(
        !lang.includes("-") && lang in defaultLocaleForLanguage ? defaultLocaleForLanguage[lang] : lang,
      ),
    ) ?? defaultLocale;

  const instance = new i18n(config);

  await instance.loadTranslations(locale, route);

  return instance.t;
}

Any page that uses translations:

{$t("some-key")}

Hey @lbguilherme - Thank you so much for your detailed answer. I stand corrected, this does indeed work.
Just one thing - It doesn't load any translations for the new route when switching routes on frontend only. I can use data.t, but not getContext('t'). Any idea why that is?

The solution above (https://github.com/sveltekit-i18n/lib/issues/106#issuecomment-1535196388) seems like a good way to avoid side-effects in load.
Shouldn't it be included in the examples?
Albeit, my use case is a pretty simple one, and I don't know whether this solution works 100% for more complex setups (e.g. what @Lobidu states here https://github.com/sveltekit-i18n/lib/issues/106#issuecomment-1642053056).
P.S. probably all of this would need reworked again after the introduction of runes.

Hey @lbguilherme - Thank you so much for your detailed answer. I stand corrected, this does indeed work.
Just one thing - It doesn't load any translations for the new route when switching routes on frontend only. I can use data.t, but not getContext('t'). Any idea why that is?

I currently have the same issue, did you manage to fix it?

Hi @CustomEntity, I've come to the same problem with translation loading, and also tried to employ the same solution of sharing the $t store via the context API — this doesn't fully work, as you're passing a new object in each context. For example, it is not possible to change the language (client side) on one page, and react to that change on another page, because you would have two different stores from two different contexts.
Please text back if you're successful using your reactive setContext solution with dynamic client side language changing (e.g. $locale = 'en' or setLocale('en')), I'd be interested to try it.

Hi @CustomEntity, I've come to the same problem with translation loading, and also tried to employ the same solution of sharing the $t store via the context API — this doesn't fully work, as you're passing a new object in each context. For example, it is not possible to change the language (client side) on one page, and react to that change on another page, because you would have two different stores from two different contexts.
Please text back if you're successful using your reactive setContext solution with dynamic client side language changing (e.g. $locale = 'en' or setLocale('en')), I'd be interested in trying it.

Hello @mtpython, I finally encountered the same problem as yours, the solution worked on a single page but not on multi-page like you. So I've stopped using SvelteKit-i18n until they fix the problem on their side, the other libraries also have the same problem so I've decided to use a temporary DIY solution that works as well as SvelteKit-i18n for my use.

Thanks for mentioning the "poly-i18n", but for my project the currently missing lazy load feature is more important than the downsides of race conditions, so until a more complete/mature solution is released, I'd resort to just accepting the current state of this library as is...
tl;dr: this issue should remain open

This worked very well for me:

Your solutions seem to work for me as well, but there is type error:
Cannot use 't' as a store. 't' needs to be an object with a subscribe method on it.

{$t('home.title')}

{$t('home.content')}


Adds Dockerfiles for CPUs as well as GPUs, closes #29

Dockerfiles for CPU as well as GPU images.

@sshuair let me know if that works for you. I would like to keep these as simple as possible with a single responsibility: packaging up robosat and it's native dependencies for either CPUs or GPUs.

Ok, I will simplify the Docker file. Is it necessary to provide the different cuda version docker image? both CUDA9.0 and CUDA9.1

Hm, good question. I think we can go with the latest versions working with PyTorch (CUDA 9.1 and cuDNN 7) since nvidia-docker should abstract driver related problems anyway, no?

@sshuair here's how to build and use these containers:
docker build -t mapbox/robosat:gpu -f docker/Dockerfile.gpu .
docker build -t mapbox/robosat:cpu -f docker/Dockerfile.cpu .

docker run -it mapbox/robosat:gpu nvidia-smi
docker run -it mapbox/robosat:gpu /app/rs -h
docker run -it mapbox/robosat:cpu /app/rs -h

I just gave it a try on a AWS p2 box and it seems to work. Anything else we should include in the Dockerfiles or do you think this is already good to go?

I agree with CUDA 9.1.
But when I use your code, I got this error:
root@bfca94f5b245:~/robosat# ./rs --help
Traceback (most recent call last):
  File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.5/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/root/robosat/robosat/tools/__main__.py", line 5, in <module>
    from robosat.tools import (
  File "/root/robosat/robosat/tools/features.py", line 11, in <module>
    from robosat.features.parking import ParkingHandler
  File "/root/robosat/robosat/features/parking.py", line 8, in <module>
    from robosat.features.core import denoise, grow, contours, simplify, featurize, parents_in_hierarchy
  File "/root/robosat/robosat/features/core.py", line 1, in <module>
    import cv2
  File "/usr/local/lib/python3.5/dist-packages/cv2/__init__.py", line 3, in <module>
    from .cv2 import *
ImportError: libgthread-2.0.so.0: cannot open shared object file: No such file or directory

and I fix that by add libglib2.0-0 , you can checkout the new version #86

I think it is necessary put the robust code into the docker image.  When we run the image, the robosat code is working directly.

Did you build the Dockerfiles and did you then run them? Because I just did and I'm not seeing the libgthread issue you are seeing. Looks like it's coming from OpenCV so that libglib dependency could make sense.

Yes. I build the modified dockerfiles and run the cpu verison. I got this error. the only different is I add git and clone from the github deps/requirements-lock.txt. It's weird.
is there a link I could pull your image?

I spent some time on this and we have automated CPU and GPU now:
https://hub.docker.com/r/mapbox/robosat/tags/
There will be latest images for the master branch and images for specific tags.
The images are quite large right now; we might want to trim them down a bit.


Dead readme links: storage provider support

This section in the readme has lots of dead links: https://github.com/codedellemc/rexray#storage-provider-support
Like this: https://github.com/codedellemc/rexray/blob/master/user-guide/storage-providers.md#aws-ebs
Should go to https://github.com/codedellemc/rexray/blob/master/.docs/user-guide/storage-providers/aws.md instead?
Or http://rexray.readthedocs.io/en/stable/user-guide/storage-providers/aws/ ?

Hello @jzaefferer,
I believe this is a caching problem. Can you try a forced refresh of the main page? Cmd->Shift->R?

This isn't a caching problem.

Thank you @jzaefferer, I dealt with something similar and figured it was in the RTFD docs. This is definitely an issue that we need to get fixed to point the main README at the right new locations.
Thank you.


SimplePreemptiveLock' object has no attribute '_lock_file'

Describe the issue:
i am build the nni whl with source code, then install it, but when i test the case in NNI/examples/trials/mnist-tfv2/config.yml, it report error
Environment:

NNI version:2.9
Training service (local|remote|pai|aml|etc): local
Client OS: centos
Server OS (for remote mode only):
Python version:3.7
PyTorch/TensorFlow version:2.9
Is conda/virtualenv/venv used?: no
Is running in Docker?: yes

Configuration:

Experiment config (remember to remove secrets!):
Search space:

Log message:

nnimanager.log:
dispatcher.log:
nnictl stdout and stderr:

[root@dcunode5 home]# nnictl create --config   NNI/examples/trials/mnist-tfv2/config.yml
[2023-04-19 06:25:21] Creating experiment, Experiment ID: 6kl8eicb
[2023-04-19 06:25:21] Starting web server...
[2023-04-19 06:25:22] WARNING: Timeout, retry...
[2023-04-19 06:25:23] WARNING: Timeout, retry...
[2023-04-19 06:25:24] ERROR: Create experiment failed
Traceback (most recent call last):
File "/root/miniconda3/bin/nnictl", line 8, in
sys.exit(parse_args())
File "/root/miniconda3/lib/python3.7/site-packages/nni/tools/nnictl/nnictl.py", line 497, in parse_args
args.func(args)
File "/root/miniconda3/lib/python3.7/site-packages/nni/tools/nnictl/launcher.py", line 91, in create_experiment
exp.start(port, debug, RunMode.Detach)
File "/root/miniconda3/lib/python3.7/site-packages/nni/experiment/experiment.py", line 135, in start
self._start_impl(port, debug, run_mode, None, [])
File "/root/miniconda3/lib/python3.7/site-packages/nni/experiment/experiment.py", line 104, in _start_impl
self.url_prefix, tuner_command_channel, tags)
File "/root/miniconda3/lib/python3.7/site-packages/nni/experiment/launcher.py", line 148, in start_experiment
raise e
File "/root/miniconda3/lib/python3.7/site-packages/nni/experiment/launcher.py", line 128, in start_experiment
Experiments().add_experiment(
File "/root/miniconda3/lib/python3.7/site-packages/nni/tools/nnictl/config_utils.py", line 109, in init
self.lock = get_file_lock(self.experiment_file, stale=2)
File "/root/miniconda3/lib/python3.7/site-packages/nni/tools/nnictl/common_utils.py", line 125, in get_file_lock
return SimplePreemptiveLock(path + '.lock', stale=stale)
File "/root/miniconda3/lib/python3.7/site-packages/nni/tools/nnictl/common_utils.py", line 98, in init
self._lock_file_name = '{}.{}'.format(self._lock_file, os.getpid())
AttributeError: 'SimplePreemptiveLock' object has no attribute '_lock_file'
How to reproduce it?:

I have same problem

I have same problem too

Same here

There was a recent update to filelock package which causes the above mentioned error.
Try to install the previous version, it should help. E.g. with pip:
pip install filelock==3.10
I hope it helps you, too!

There was a recent update to filelock package which causes the above mentioned error.
Try to install the previous version, it should help. E.g. with pip: pip install filelock==3.10
I hope it helps you, too!
thanks, solved it by this way.

There was a recent update to filelock package which causes the above mentioned error.
Try to install the previous version, it should help. E.g. with pip: pip install filelock==3.10
I hope it helps you, too!
thanks, solved it by this way.

Thank you! this works well~


Customer feedback -

Type of issue
Typo
Feedback
hKmdCpuEvent
[in] Handle to the KMD CPU event object.
This should be out. Refer to <WDK_KIT>\shared\d3dkmddi.h
hKmdCpuEvent
[out] Handle to the KMD CPU event object.
Page URL
https://learn.microsoft.com/en-us/windows-hardware/drivers/ddi/d3dkmddi/ns-d3dkmddi-dxgkarg_createcpuevent
Content source URL
https://github.com/MicrosoftDocs/windows-driver-docs-ddi/blob/staging/wdk-ddi-src/content/d3dkmddi/ns-d3dkmddi-dxgkarg_createcpuevent.md
Author
@lorihollasch

Great catch, @sandilya-xilinx! Thanks for reporting this - I've updated the page.


Implement clipboard cut & copy on text_input widget

I implemented "cut" & "copy" on TextInput using a crate "clipboard".
As I know there is a clipboard project (window_clipboard), I'm not sure this is okay.
And I changed behavior of TextInput "while pressing copy_paste_modifier_key".
I guess this is expected behavior for most case on TextInput though,..
(I tested only on macOS 10.15.6)
Discussion @ #295

As I mentioned in #295, we are not ready to write code for this yet.
We need to figure out a good cross-platform clipboard API on top of a raw-window-handle.


support executioner.execute(Generator | GeneratorFn)

Shortcut to execute Generators or Generator Functions without instantiating a task.
Optionally make it possible to run statically, as Executioner.execute(...)

worked on here

Working on execute-gen-genfn-directly.

Feature added in #3.


Lexicographic string comparison

🚀 Feature Proposal
JavaScript supports comparing strings: '2018-01-01' < '2019-01-01'. Jest should pass that through.
Motivation
I want to be able to easily compare ISO8601 dates.
Example
expect(date).toBeGreaterThan('2020-06-01')
expect(doc.updatedAt).toBeGreaterThan(doc.createdAt);

Pitch

Why does this feature belong in the Jest core platform?
I have submitted it to jest-extended already.

I think this would be better as a separate matcher to avoid confusion around why assertions with strings pass and to ensure users are explicit about what type they expect in the matcher. And because of its rare use cases, I would say it's a better fit for jest-extended.

I have the exact same use case. According to https://riptutorial.com/javascript/example/5388/comparing-strings-lexicographically you can use localeCompare() for lexicographical comparisons:
var a = "hello";
var b = "world";

console.log(a.localeCompare(b)); // -1

And with Jest:
var a = "hello";
var b = "world";

expect(a.localeCompare(b)).toBeLessThan(0) // true


Repo sync for protected CLA branch

The pull request is created from main638065730852655395sync_temp to main to fix git push error for protected CLA branch

Learn Build status updates of commit a20d1aa:
:white_check_mark: Validation status: passed
For more details, please refer to the build report.
Note: Broken links written as relative paths are included in the above build report. For broken links written as absolute paths or external URLs, see the broken link report.
For any questions, please:Try searching the learn.microsoft.com contributor guidesPost your question in the Learn support channel


Flatten files at destination

How to flatten directories when when copy files?
target(dir, {depth: *}), depth option has no effect in version 2^.

That is correct. The depth option from fly.target was removed in v2.
It now exists as a separate package (fly-flatten) for those who need it.

Thanks for the issue. You reminded me that I needed to release this plugin. 😄

thanks for looking, but issue is still there, and I think it's related to task.target and glob replacement,
below is example
 yield fly 		.source("jspm_packages/npm/font-awesome*/fonts/*.{woff2,woff,svg,eot,ttf,otf}") 		.flatten() 		.target(${dist}/fonts/font-awesome);
expected: /dist/fonts/font-awesome/.
output (from above code<EMAIL_ADDRESS>

No problem!
Yes, that's actually expected. fly-target begins reading from the first instance of *. So you'll need to specify the full font-awesome string.
yield fly
  .source("jspm_packages/npm/font-awesome@4.7.0/fonts/*.{woff2,woff,svg,eot,ttf,otf}")
  .flatten()
  .target("dist/fonts/font-awesome");


(PUP-6919) Add :cwd option to Puppet::Util::Execution.execute + use it in Exec provider

CLA signed by all contributors.

Since this is extending the Puppet::Util::Execution.execute interface, this will be available for functions and hiera backends that run during compilation in JRuby, right? Do you know if this if/how this would affect Puppet Server's execution backend?

@justinstoller I have no idea. I don't think it should affect it because the default behavior is to use the PWD when the option's not provided, which is how it was done before. Who would be a good person to ask about that to confirm?

Puppet Server sets the ExecutionStub's current_value so when running in a master execute_posix and execute_windows are never called.
However, Puppet Server only honors combine and failonfail options. Though it would be possible to plumb this option through if it was desired (see our Java code and the underlying library's interface). If not, at least the documentation should say that this option is only available on the agent (t&ps) and cannot be used on the master (regular functions, hiera backends, report processors).

Ok, then I don't think this will affect anything in Puppetserver b/c the cwd option is used in execute_posix and execute_windows -- execute just sets the default value to Dir.pwd.
Agreed on the documentation. What documentation would I need to update? Is that something that'll be added from the ticket's release notes? Comments in the method itself?

jenkins please test this on windows10ent-64a,windows10ent-32a,windows2008r2-64a,windows2012r2-64a,windows2012r2_ja-64a%7Blocale=ja%7D,windows2016-64a

jenkins please test this on windows10ent-64a,windows10ent-32a,windows2008r2-64a,windows2012r2-64a,windows2012r2_ja-64a%7Blocale=ja%7D,windows2016-64a,redhat7-64a,aix71-POWERfa,solaris10-64a,solaris11-64a,ubuntu1604-32a,osx1012-64a

Status on the PR test failures:

The new acceptance tests failed on all the POSIX platforms save for RHEL. This is an issue with how I retrieve the CWD.
Some of the crontab tests failed on AIX and Solaris 11, b/c the execute function defaults to the PWD for the Puppet process which is /root -- these tests result in a permission denied error when running the execute commands using the crontab user. Fix for this is to just remove the Dir.pwd default and don't pass in a cwd when calling Kernel.exec or Win32::Process.create if it is not provided. I'll probably update the cwd acceptance tests to add a test for running commands with a different user so this is caught at the right level.

I'll work on this later.

Looks like the tests hung on win2008: https://jenkins-platform.delivery.puppetlabs.net/job/platform_puppet-agent-extra_puppet-agent-integration-suite_pr/576/RMM_COMPONENT_TO_TEST_NAME=puppet,SLAVE_LABEL=beaker,TEST_TARGET=windows2008r2-64a/console

jenkins please test this on windows10ent-64a,windows10ent-32a,windows2008r2-64a,windows2012r2-64a,windows2012r2_ja-64a%7Blocale=ja%7D,windows2016-64a,redhat7-64a,aix71-POWERfa,solaris10-64a,solaris11-64a,ubuntu1604-32a,osx1012-64a

Updated the PR to fix the previous PR test failures. The failed tests passed on all the failed platforms when I ran them locally. Also decided not to add an acceptance test for the "can a local, non-Admin user run commands w/ the Exec resource" -- the set-up across all of our platforms is more complicated than the value that test would add, especially when we already catch this case in our crontab tests.

PR tests passed save for Win 2008 which timed out. Don't think that has anything to do with the changes here though.

Updated the PR with a new commit that contains all of the updates I made. This commit will be squashed prior to a merge.
I talked with @glennsarti about File.directory? and UNC paths. Given that there's a lot of different Windows versions out there + all kinds of UNC paths (e.g. webdav, long form, UNCW), it is better (and simpler) to just let Process.create take care of this for us instead of testing all possible combinations to see if File.directory? works with them.

jenkins please test this on windows10ent-64a,windows10ent-32a,windows2008r2-64a,windows2012r2-64a,windows2012r2_ja-64a%7Blocale=ja%7D,windows2016-64a,redhat7-64a,aix71-POWERfa,solaris10-64a,solaris11-64a,ubuntu1604-32a,osx1012-64a

I'll review more fully in the morning, but the reasoning to defer error handling to the OS makes sense, and it looks like your exception on win32 is about what we'd want


Adding *.xcworkspace to gitignore

React Native version: 0.60.0 RC2
Steps To Reproduce

react-native init RN060 --version react-native@next
go to project directory and open .gitignore file

Describe what you expected to happen:
running pod install causes a new [PROJECT_NAME].xcworkspace has been created.
already just project.xcworkspace has been ignored in .gitingore file. I think it's better to replace project.xcworkspace with *.xcworkspace to ignore pod creation too.

👋 there - thanks for raising it.
I looked a bit into it, and it seems that that line in the gitignore was caused by a really old commit that was generating via a yeoman template -> https://github.com/facebook/react-native/commit/f83675d1915b5e77638c117c82f8641cea367ffe
I actually think that you don't want to have the *.xcworkspace to be ignored, but I may be wrong.
Would you mind opening a PR with your solution (https://github.com/facebook/react-native/blob/master/template/_gitignore#L23) this is the file, so that it can be looked into / discussed more?

@kelset
I already submit a PR for it, but it closes by @cpojer and I didn't know what's the exact reason for it.
I raised this issue according to current gitignore file. I thought if the project.xcworkspace must be ignored, so probably we don't need the new  [PROJECT_NAME].xcworkspace file generated by pod install command too, because it can be regenerated every time someone creates or clones a react-native project, e.g. we may need to run pod install after npm install.
What do you think?

Recently I'm using react-native-firebase in my project and I use pods for IOS installation steps, so it creates a new .xcworkspace with my project name and I already have two .xcworkspace files. (let assume my project name is Test)

project.xcworkspace

Test.xcworkspace

From react-native-firebase documentation:

You need to use the ios/[YOUR APP NAME].xcworkspace instead of the ios/[YOUR APP NAME].xcproj file from now on.

I looked into 0.60.x-RC changelogs and I see that pods will be supported by default in 0.60 version. So I thought maybe it's necessary to ignore all .xcworkspace files instead of project.xcworkspace file only because of any cases pod install creates more than one .xcworkspace files like mine.

I looked at your PR, and as I mentioned, we should simply remove that line because that file is actually something that you should have in your git history (we are actually taking care of that in another PR, here -> https://github.com/facebook/react-native/pull/25451).
Related to the fact that you have two .xcworkspace, I think that something went wrong with your configuration 🤔 there should be only one.

Related to the fact that you have two .xcworkspace, I think that something went wrong with your configuration 🤔 there should be only one.

I have two because I currently using RN0.59.9 and as I mentioned before the second file has been created because of pod install command in ios installation steps of react-native-firebase, they already mention on their documentation that there will be two .xcworkspace files on my repository after the command.

You need to use the ios/[YOUR APP NAME].xcworkspace instead of the ios/[YOUR APP NAME].xcproj file from now on.

So, can you approve this? Do I must revert my project's .gitignore file to be project.xcworkspace and commit the .xcworkspace file created by pod install? and I wait for 0.60 stable release for a stable solution?

this is my ios directory after pod install

Actually, it's my bad, I didn't read the files extension totally :D (I'm sorry). one of them is .xcworkspace and the other is .xcodeproj, and according to your advice I will remove the *.xcworkspace line  (or project.xcworkspace from original template) from my .gitignore file

we should simply remove that line because that file is actually something that you should have in your git history

No worries 🤗


[DOUBT] Performance expectations

Does it take advantage of multi threading or something?

In the new version, everything has been aligned with asynchronous operations. We are using Playwright, and the result is amazing, perhaps the best way to achieve super speed. However, we are currently working on the scraping engine, which promises to be a significant undertaking. We are investing time to optimize multi-processing, multi-threading, and asynchronous techniques to create a robust system. For now you can use arun_many function to simply use aync I/O parallelism. Anyway stay tuned for the upcoming release of the scraper, which will deliver a remarkable multitasking experience for crawling numerous links or entire websites.
Right now you can try something like this:
# File: async_webcrawler_multiple_urls_example.py

import asyncio
from crawl4ai import AsyncWebCrawler, NoExtractionStrategy, RegexChunking

async def main():
    # Initialize the AsyncWebCrawler
    async with AsyncWebCrawler(verbose=True) as crawler:
        # List of URLs to crawl
        urls = [
            "https://example.com",
            "https://python.org",
            "https://github.com",
            "https://stackoverflow.com",
            "https://news.ycombinator.com"
        ]

        # Set up crawling parameters
        word_count_threshold = 100

        # Run the crawling process for multiple URLs
        results = await crawler.arun_many(
            urls=urls,
            word_count_threshold=word_count_threshold,
            bypass_cache=True,
        )

        # Process the results
        for result in results:
            if result.success:
                print(f"Successfully crawled: {result.url}")
                print(f"Title: {result.metadata.get('title', 'N/A')}")
                print(f"Word count: {len(result.markdown.split())}")
                print(f"Number of links: {len(result.links.get('internal', [])) + len(result.links.get('external', []))}")
                print(f"Number of images: {len(result.media.get('images', []))}")
                print("---")
            else:
                print(f"Failed to crawl: {result.url}")
                print(f"Error: {result.error_message}")
                print("---")

if __name__ == "__main__":
    asyncio.run(main())

Hey Nice to know this function, I just have a small doubt in the implementation of this arun_many,
what if i want to write the extracted_content of all the urls in my docs and store the failed scarp url into a list and pass on to another function,
For example in this mannerism:
try:
logger.info(f"Urls:{urls}")
async with AsyncWebCrawler(verbose=True) as crawler:
strategy = LLMExtractionStrategy(
provider="groq/llama-guard-3-8b",
api_token=os.getenv('GROQ_API_KEY'),
schema=PageSummary.model_json_schema(),
extraction_type="schema",
apply_chunking=True,
instruction=(......
),
bypass_cache=True,
)
for url in urls:
try:
result = await crawler.arun(
url=url,
word_count_threshold=100,
extraction_strategy=strategy,
bypass_cache=True,
process_iframe=True,
)
                if result.success:
                    try:
                        extracted_content_json = json.loads(result.extracted_content)
                        save_to_word_incremental(extracted_content_json, url, docx_path)
                        remaining_urls.remove(url)
                        logger.info(f"remaining_urls: {remaining_urls}")
                    except json.JSONDecodeError as e:
                        logger.error(f"Failed to decode extracted content for {url}: {e}")
                else:
                    logger.error(f"Error in crawling {url}, {result.error_message}")

            except Exception as crawl_error:
                logger.error(f"Failed to crawl {url}, error: {crawl_error}--> redirecting to different webscraping service")
                await scrap_webpages(remaining_urls, docx_path)
                return docx_path
    return docx_path

except Exception as e:
    logger.error(f"Unexpected error with webscraping service {e}")
    return docx_path

Its someting like this
then can i just proceed with the replacment of the arun_many?
in results we get all the details right?? So in that i should append all the extracted_content and add it to the doc?
Am i right with this understand flow?

@Mahizha-N-S If I understand your question, you can still call the arun_many method to perform multiple parallel crawling, which is similar to what you're doing here. Instead of using a four-loop, it utilizes parallelism with asynchronous operations. At the end of the day, you'll have a list of all crowd results, and you can check the success flag to see whether it's true or false. Those that are successful can be added to your file, while those that fail can be addressed using different solutions. Each failure also comes with a message property to explain what specifically went wrong. Let me know if this is helpful.


multi_az Computed: true

Change description
multi_az is computed now.
Type of change

[x] Bug fix (fixes an issue)
[ ] New feature (adds functionality)

Checklists
Development

[ ] Pull requests may not be submitted to the master branch (use develop instead) - or they will be closed.
[ ] Lint rules pass locally
[ ] Application changes have been tested thoroughly
[ ] Automated tests covering modified code pass

Security

[ ] Security impact of change has been considered
[ ] Code follows company security practices and guidelines

Code review

[ ] Pull request has a descriptive title and context useful to a reviewer.
[ ] "Ready for review" label attached and reviewers assigned
[ ] Changes have been reviewed by at least one other contributor
[ ] Pull request linked to task tracker where applicable

Task linked: DUPLO-9131 TF: Multi AZ value changes should not be shown in Plan for Aurora Cluster db


Quest to Subquest alteration

There's no simple way of transforming a side-quest into a sub-quest of a larger quest. It would be very helpful to make it possible to do so through the interface.

I would also love to see this functionality.
After making a bunch of quests, it occurred to me I could have grouped some of them under 1 "main" quest. A way to change this after the fact would be a nice feature to have.

@typhonrt Just finished watching the video you did on the rework. (Thank you for that btw) Player creation and Trusted Player edit brought me back to this issue. I know we spoke somewhat about this on Discord.
Just thought of a highly useful quest workflow (for some games) if this was an available feature. Trusted Player creates quest, adds objectives, etc. GM knows that this is actually a sub-quest of The Main Quest. GM can set this new quest as a sub-quest of The Main Quest. Players do not see this is a subquest since that's how you have it setup now, but GM does. This allows the GM to more easily track those subquests as part of the main and saves the GM a little effort in not having to create subquests ahead of time.
Most importantly, it allows players the ability to create them as the campaign unfolds and gives them more agency and participation as well as letting them log the subquests and details as they see it. I find this to be invaluable for not only player involvement, but it also shows the players' level of understanding. The GM now knows if they are seeing events differently, missing stuff, etc.. I also personally find it easier to follow things and kind of reinforce events in my memory if I write it down myself.
So a second plea with a little more, hopefully constructive, info on the value of this feature. :-)

@Shuggaloaf Yeah the way I'm thinking of implementing this feature is to provide a selection icon next to where the parent quest area is that is only visible for GM level users. Trusted players w/ edit won't see this icon and can't reassign quests / subquest connections. Click on the icon and a dialog pops up with an auto-complete area to type in the new potential parent quest name which then populates a drop down box. Select that new parent quest and FQL goes about reassigning the quest links.
Do consider joining the TyphonJS Discord too which is a great place to brainstorm new ideas around all of this and other module extensions. That might provide a better spitballing forum then enhancement issues can be filed as appropriate, etc.

Do consider joining the TyphonJS Discord too which is a great place to brainstorm new ideas around all of this and other module extensions. That might provide a better spitballing forum then enhancement issues can be filed as appropriate, etc.

Thanks for the Discord invite! There are times when a spitballing-style discussion would definitely be more appropriate and I was actually thinking the same thing a few days ago. I had previously commented on this thread so just wanted to come back and mention that here since the issue already was opened.
To clarify for all of us - when you say:

Click on the icon and a dialog pops up with an auto-complete area to type in the new potential parent quest name which then populates a drop down box
It sounds like this is basically saying - Step 1: Type Parent Quest name; Step 2: Parent Quest from Step 1 is now available in a dropdown and can be selected.
Is that correct? If so, what if the Parent Quest already exists?

Thanks @typhonrt

It sounds like this is basically saying - Step 1: Type Parent Quest name; Step 2: Parent Quest from Step 1 is now available in a dropdown and can be selected.
Is that correct? If so, what if the Parent Quest already exists?

The select box will populate with existing quests based on autocomplete. So, it's not creating a new quest, but assigning the parent quest by selecting a quest that already exists. The autocomplete angle to search for existing quests is pertinent especially when there are many quests to choose from. IE it could get unwieldy otherwise to list all potential quest targets for the assignment.
I'll likely be using tail-select or similar more advanced select component.

OK I got what you mean now - the dropdown box itself allows autocomplete typing. I was thinking you meant 2 separate fields, a text input box and a dropdown. Sounds like a great solution! You always seem to go the extra little bit to make things more use-friendly. Definitely appreciate that!

Would this support promoting or altering subquests to quests?
(I can see a future where all quests are just quests, and any quest can have an arbitrary link to a single other quest that is effectively its parent, which, when that is added effectively turns it into a subquest, but really its just a quest with a nominated linked quest.)

Hi @Jagusti! Indeed all quests are just a plain quest. They become a subquest in the GUI when they have a "parent quest". Indeed I'd like to organize things in the future where there is more that a one to many connection. Luckily that is just opening up the way the data is stored.
With this initial quest to subquest alteration enhancement though there will be a way to reassign the parent of a quest. Remove the parent and the "subquest" becomes a new top level parent. Add a parent then that quest becomes a subquest.


the hamburger button should have a toggle feature for list view

list view button should worked as hamburger toggle because when i started this app ,i am expecting for this behaviour.

Sugar platform use it's own UI concepts.
It could be disturbing for adults familiar with other concepts but it's very easy to understand by children.

@llaske  thank you for explaination


leaked temp files when unzip failed

unzip sometimes fails in func (f *File) ReadZipReader(r *zip.Reader) when reading in large xlsx while there's not sufficient disk space, and the related temp file won't be cleared in this case.
a draft fix would be something like:
			tempFile, err := f.unzipToTemp(v)
			if tempFile != "" {
				f.tempFiles.Store(fileName, tempFile)
			}
			if err == nil {
				continue
			}

this might be related to #1062

Thanks for your issue. Could you provide more details about this, such as an attachment to reproduce this issue?

Thanks for your issue. This issue has been fixed, please try to upgrade the master branch code, and this patch will be released in the next version.


I cannot adjust the :colorscheme onedark

nvim --version: 0.9.0
terminal emulator and version: iTerm2 build 3.4.19
Operating system/version: macOS/Ventura 13.3.1
Have you read and followed all steps in the doc: Yes, I read the document thoroughly.
Output of command set runtimepath:

runtimepath=~/.config/nvim,/usr/local/etc/xdg/nvim,/etc/xdg/nvim,~/.local/share/nvim/site,~/.local/share/nvim/site/pack/packer/opt/vim-swap,~/.local/share/
nvim/site/pack/packer/opt/indent-blankline.nvim,~/.local/share/nvim/site/pack/packer/opt/vim-matchup,~/.local/share/nvim/site/pack/packer/opt/whitespace.nvim
,~/.local/share/nvim/site/pack/packer/opt/cmp-path,~/.local/share/nvim/site/pack/packer/opt/fidget.nvim,~/.local/share/nvim/site/pack/packer/opt/nvim-lspconf
ig,~/.local/share/nvim/site/pack/packer/opt/cmp-nvim-lsp,~/.local/share/nvim/site/pack/packer/opt/cmp-omni,~/.local/share/nvim/site/pack/packer/opt/cmp-buffe
r,~/.local/share/nvim/site/pack/packer/opt/cmp-emoji,~/.local/share/nvim/site/pack/packer/opt/nvim-cmp,~/.local/share/nvim/site/pack/packer/opt/lspkind-nvim,
~/.local/share/nvim/site/pack/packer/opt/vim-repeat,~/.local/share/nvim/site/pack/packer/opt/nvim-web-devicons,~/.local/share/nvim/site/pack/packer/opt/buffe
rline.nvim,~/.local/share/nvim/site/pack/packer/opt/which-key.nvim,~/.local/share/nvim/site/pack/packer/opt/dashboard-nvim,~/.local/share/nvim/site/pack/pack
er/opt/lualine.nvim,~/.local/share/nvim/site/pack/packer/opt/open-browser.vim,~/.local/share/nvim/site/pack/packer/opt/targets.vim,~/.local/share/nvim/site/p
ack/packer/opt/hop.nvim,~/.local/share/nvim/site/pack/packer/opt/vim-sandwich,~/.local/share/nvim/site/pack/packer/opt/unicode.vim,~/.local/share/nvim/site/p
ack/packer/opt/vim-commentary,~/.local/share/nvim/site/pack/packer/opt/vim-highlighturl,~/.local/share/nvim/site/pack/packer/opt/vim-indent-object,~/.local/s
hare/nvim/site/pack/packer/opt/gitlinker.nvim,~/.local/share/nvim/site/pack/packer/opt/vim-fugitive,~/.local/share/nvim/site/pack/packer/opt/nvim-notify,~/.l
ocal/share/nvim/site/pack/packer/opt/nvim-treesitter,~/.local/share/nvim/site/pack/*/start/*,~/.local/share/nvim/site/pack/packer/opt/everforest,~/.local/sha
re/nvim/site/pack/packer/opt/committia.vim,~/.local/share/nvim/site/pack/packer/opt/wilder.nvim,~/.local/share/nvim/site/pack/packer/opt/firenvim,~/.local/sh
are/nvim/site/pack/packer/opt/packer.nvim,/usr/local/share/nvim/site,/usr/share/nvim/site,/usr/local/Cellar/neovim/0.9.0/share/nvim/runtime,/usr/local/Cellar
/neovim/0.9.0/lib/nvim,~/.local/share/nvim/site/pack/packer/opt/vim-matchup/after,~/.local/share/nvim/site/pack/packer/opt/cmp-path/after,~/.local/share/nvim
/site/pack/packer/opt/cmp-nvim-lsp/after,~/.local/share/nvim/site/pack/packer/opt/cmp-omni/after,~/.local/share/nvim/site/pack/packer/opt/cmp-buffer/after,~/
.local/share/nvim/site/pack/packer/opt/cmp-emoji/after,~/.local/share/nvim/site/pack/packer/opt/vim-sandwich/after,~/.local/share/nvim/site/pack/packer/opt/e
verforest/after,/usr/share/nvim/site/after,/usr/local/share/nvim/site/after,~/.local/share/nvim/site/after,/etc/xdg/nvim/after,/usr/local/etc/xdg/nvim/after,
~/.config/nvim/after

Describe the bug
Steps to reproduce the issue:

:colorscheme onedark/onelight/onedark_dark/onedark_vivid

Expected behavior
I expected to change my colorscheme.
Screenshots

Additional context

Oh, I see. It wasn't just my problem.
I should have done some more searching. I apologize for any inconvenience.
Thank you for your kind reply.


receiver-port config setting

Does the receiver-port config setting work? I use a custom port (30054) and I have to go through the source code of each release and replace every instance of 30005 with 30054 to get it to work. Thanks!

Is this a piaware sdcard image? receiver-type relay requires configuration of other software that is only done on a sdcard image, not a package install. If you are not using the sdcard image, use receiver-type other and arrange your own configuration.

Yes it's a package install and that did the trick.  Thanks!


htmlfile ActiveX clipboard access is broken

It's fine in version 1.0.0 but broken in 1.0.1...
var doc = new ActiveXObject('htmlfile');
var text = doc.parentWindow.clipboardData.getData('Text');
if (typeof text == 'string') console.log(text);

Error: Spider Monkey Panel v1.0.1 ({C60D7A42-D3FE-4423-ACDA-815823F29935})
doc.parentWindow.clipboardData is undefined

Darn, wonder if I can somehow differentiate between arrays and objects that have length property...


bug: Bottom area padding for accept button on iPhone X

Screenshot
iPhone 8

iPhone X

Can one of the admins verify this patch?


[ACS][Callautomation] Skip Recorded test and delete Event record until test proxy to work with event recordings

API change check
API changes are not detected in this pull request.


Add @jameshowison as an admin on the UT hub

This adds @jameshowison as an admin on the UT hub that @yuvipanda just deployed.

Ah, I misinterpreted. I thought I was to add James....

That's fine too - we've just often explicitly listed the community representatives in the config and let them add others. If you've already added them then this will not change the hub itself, only make it more explicit


No exception support

There is currently no support for Exception handling. Known examples:

IndexError: if wiki search contains no results, stream crashes
DisambiguationError: If top result links to disambiguation page, stream crashes

Added exception handling in most recent commit


Ansible fails when using --port in Kubeflix oc export svc with cdk-2.2.0

Hi, in an effort to get this app running with the cdk-2.2.0, I used the provided Ansible playbook. The playbook fails to execute due to the --port option in oc export service ... --port in ansible-playbook.yml.
TASK: [Install Kubeflix] ******************************************************
failed: [localhost] => {"changed": true, "cmd": "oc create -f http://central.maven.org/maven2/io/fabric8/kubeflix/packages/kubeflix/1.0.17/kubeflix-1.0.17-kubernetes.yml && oc new-app kubeflix && oc expose service hystrix-dashboard --port=8080 --hostname=hystrix-dashboard-helloworld-msa.rhel-cdk.<IP_ADDRESS>.xip.io && oc policy add-role-to-user admin system:serviceaccount:helloworld-msa:turbine", "delta": "0:00:03.165838", "end": "2016-09-22 20:39:26.293465", "failed": true, "failed_when_result": true, "rc": 1, "start": "2016-09-22 20:39:23.127627", "stdout_lines": ["template \"kubeflix\" created", "--> Deploying template kubeflix for \"kubeflix\"", "--> Creating resources ...", "    serviceaccount \"ribbon\" created", "    serviceaccount \"turbine\" created", "    service \"hystrix-dashboard\" created", "    service \"turbine-server\" created", "    replicationcontroller \"hystrix-dashboard\" created", "    replicationcontroller \"turbine-server\" created", "--> Success", "    Run 'oc status' to view your app."], "warnings": []}
stderr: error: cannot use --port when generating a route
stdout: template "kubeflix" created
--> Deploying template kubeflix for "kubeflix"
--> Creating resources ...
    serviceaccount "ribbon" created
    serviceaccount "turbine" created
    service "hystrix-dashboard" created
    service "turbine-server" created
    replicationcontroller "hystrix-dashboard" created
    replicationcontroller "turbine-server" created
--> Success
    Run 'oc status' to view your app.

FATAL: all hosts have already failed -- aborting

And here's the error in isolation:
[vagrant@rhel-cdk ~]$ oc expose service hystrix-dashboard --port=8080 --hostname=hystrix-dashboard-helloworld-msa.rhel-cdk.<IP_ADDRESS>.xip.io
error: cannot use --port when generating a route

This was a bug in the oc version that comes with CDK. I used oc 1.3.0 (because I have ansible installed in my box instead of installing it inside CDK) and I couldn't reproduce this error anymore. Please use oc version 1.3 from outside CDK.


Add SSH pub key tests for ECDSA and ED25519 keys

Related to https://github.com/deis/workflow-cli/pull/260, this PR adds SSH public key testing for ECDSA and ED25519.

Thanks for the contribution! Please ensure your commits follow our style guide. This code will be tested once a Deis maintainer reviews it.

Current coverage is 87.88% (diff: 100%)

Merging #1109 into master will increase coverage by 0.13%

@@             master      #1109   diff @@
==========================================
  Files            42         42
  Lines          3639       3639
  Methods           0          0
  Messages          0          0
  Branches        623        623
==========================================
+ Hits           3193       3198     +5
+ Misses          295        290     -5
  Partials        151        151

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Jenkins, add to whitelist.
@seanknox could you rebase this against current master?

sure thing.