The kiwicutter from unbabel

some confusions

hello, i got some questions when i read exercises.md. Among it, you suggest that we can change the network architecture, but how to operate? I don't quite understand.
Good luck for you.

Error in training the tutorial NuQE yaml config when enable GPU

Hi,

I was trying to follow the tutorial in the notebook. When I change the yaml config gpu-id: -1 to gpu-id: 0 which should enable GPU training, an error occured. Following are the log output and the error info:

2020-05-24 13:00:57.181 [root setup:380] This is run ID: c5854f3d72844dd8b842c49c4a29f9fc
2020-05-24 13:00:57.181 [root setup:383] Inside experiment ID: 0 (None)
2020-05-24 13:00:57.182 [root setup:386] Local output directory is: runs/nuqe
2020-05-24 13:00:57.182 [root setup:389] Logging execution to MLflow at: None
2020-05-24 13:00:57.186 [root setup:395] Using GPU: 0
2020-05-24 13:00:57.186 [root setup:400] Artifacts location: None
2020-05-24 13:00:57.193 [kiwi.lib.train run:154] Training the NuQE model
2020-05-24 13:00:59.819 [kiwi.lib.train run:187] NuQE(
  (_loss): CrossEntropyLoss()
  (source_emb): Embedding(6437, 50, padding_idx=1)
  (target_emb): Embedding(7493, 50, padding_idx=1)
  (embeddings_dropout): Dropout(p=0.5, inplace=False)
  (linear_1): Linear(in_features=300, out_features=400, bias=True)
  (linear_2): Linear(in_features=400, out_features=400, bias=True)
  (linear_3): Linear(in_features=400, out_features=200, bias=True)
  (linear_4): Linear(in_features=200, out_features=200, bias=True)
  (linear_5): Linear(in_features=400, out_features=100, bias=True)
  (linear_6): Linear(in_features=100, out_features=50, bias=True)
  (linear_out): Linear(in_features=50, out_features=2, bias=True)
  (gru_1): GRU(400, 200, batch_first=True, bidirectional=True)
  (gru_2): GRU(200, 200, batch_first=True, bidirectional=True)
  (dropout_in): Dropout(p=0.0, inplace=False)
  (dropout_out): Dropout(p=0.0, inplace=False)
)
2020-05-24 13:00:59.819 [kiwi.lib.train run:188] 2347752 parameters
2020-05-24 13:00:59.819 [kiwi.trainers.trainer run:75] Epoch 1 of 3
2020-05-24 13:01:13.122 [kiwi.metrics.stats log:60] tags_F1_MULT: 0.0275, tags_F1_OK: 0.9294, tags_F1_BAD: 0.0296, tags_CORRECT: 0.8683, loss_loss: 892.0779
2020-05-24 13:01:26.385 [kiwi.metrics.stats log:60] tags_F1_MULT: 0.1496, tags_F1_OK: 0.9225, tags_F1_BAD: 0.1622, tags_CORRECT: 0.8582, loss_loss: 835.9351
Batches: 100%|██████████████████████████| 211/211 [00:27<00:00,  7.58 batches/s]
2020-05-24 13:01:27.717 [kiwi.metrics.stats log:60] tags_F1_MULT: 0.2363, tags_F1_OK: 0.8934, tags_F1_BAD: 0.2645, tags_CORRECT: 0.8139, loss_loss: 786.3296
2020-05-24 13:01:29.716 [kiwi.metrics.stats log:60] EVAL_tags_F1_MULT: 0.2828, EVAL_tags_F1_OK: 0.9003, EVAL_tags_F1_BAD: 0.3141, EVAL_tags_CORRECT: 0.8259, EVAL_loss_loss: 789.3109
2020-05-24 13:01:29.717 [root save:183] Saving training state to runs/nuqe/epoch_1
2020-05-24 13:01:29.829 [root save_latest:241] Saving training state to runs/nuqe/temp_latest_epoch
2020-05-24 13:01:29.830 [kiwi.trainers.callbacks _remove_snapshot:178] Removing previous snapshot: runs/nuqe/latest_epoch
2020-05-24 13:01:29.830 [kiwi.trainers.callbacks save_latest:252] Moving runs/nuqe/temp_latest_epoch to runs/nuqe/latest_epoch
Traceback (most recent call last):
  File "/opt/conda/bin/kiwi", line 8, in <module>
    sys.exit(main())
  File "/opt/conda/lib/python3.7/site-packages/kiwi/__main__.py", line 22, in main
    return kiwi.cli.main.cli()
  File "/opt/conda/lib/python3.7/site-packages/kiwi/cli/main.py", line 71, in cli
    train.main(extra_args)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/cli/pipelines/train.py", line 142, in main
    train.train_from_options(options)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/lib/train.py", line 123, in train_from_options
    trainer = run(ModelClass, output_dir, pipeline_options, model_options)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/lib/train.py", line 204, in run
    trainer.run(train_iter, valid_iter, epochs=pipeline_options.epochs)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/trainers/trainer.py", line 79, in run
    self.checkpointer(self, valid_iterator, epoch=epoch)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/trainers/callbacks.py", line 115, in __call__
    predictions = trainer.predict(valid_iterator)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/trainers/trainer.py", line 167, in predict
    model_pred = self.model.predict(batch)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/models/model.py", line 137, in predict
    mask = self.get_mask(batch, input_key)
  File "/opt/conda/lib/python3.7/site-packages/kiwi/models/model.py", line 205, in get_mask
    input_tensor != pad_id, dtype=torch.uint8
RuntimeError: expected device cuda:0 but got device cpu

Thanks!
Tim

Kiwi has no load_model attribute

in
----> 1 model = kiwi.load_model('trained_models/estimator_en_de.torch/estimator_en_de.torch')

AttributeError: module 'kiwi' has no attribute 'load_model'

while running using_kiwi.pynb as py file getting error in utils.download_kiwi => 'utils' has no attribute 'download_kiwi'

File "translationConfidenceScore.py", line 16, in
utils.download_kiwi(OK_url)
AttributeError: module 'utils' has no attribute 'download_kiwi'

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some confusions

Error in training the tutorial NuQE yaml config when enable GPU

Kiwi has no load_model attribute

while running using_kiwi.pynb as py file getting error in utils.download_kiwi => 'utils' has no attribute 'download_kiwi'

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