PS Very New Flair User :)
Can't increase the num_workers...
To Reproduce
document_embeddings = DocumentRNNEmbeddings(word_embeddings,
hidden_size=512,
rnn_layers = 1,
bidirectional=True,
dropout = 0.23,
reproject_words=True,
reproject_words_dimension=256,
)
classifier = TextClassifier(document_embeddings, label_dictionary=corpus.make_label_dictionary(), multi_label=False)
trainer = ModelTrainer(classifier, corpus)
trainer.train('./stacked_embeddings/',num_workers=16, max_epochs=10, mini_batch_size= 32,
learning_rate=0.1, anneal_factor=0.5, train_with_dev=True)
Expected behavior
I expected to allow the Trainer.train() to increase the num_workers as such.. reference
Traceback
```'2019-05-28 18:15:22,482 ----------------------------------------------------------------------------------------------------
TypeError Traceback (most recent call last)
1 trainer = ModelTrainer(classifier, corpus)
2 trainer.train('./stacked_embeddings/',num_workers=16, max_epochs=10, mini_batch_size= 32,
----> 3 learning_rate=0.1, anneal_factor=0.5, train_with_dev=True)
~/.local/lib/python3.7/site-packages/flair/trainers/trainer.py in train(self, base_path, evaluation_metric, learning_rate, mini_batch_size, eval_mini_batch_size, max_epochs, anneal_factor, patience, anneal_against_train_loss, train_with_dev, monitor_train, embeddings_in_memory, checkpoint, save_final_model, anneal_with_restarts, test_mode, param_selection_mode, *kwargs)
80 weight_extractor = WeightExtractor(base_path)
81
---> 82 optimizer = self.optimizer(self.model.parameters(), lr=learning_rate, *kwargs)
83 if self.optimizer_state is not None:
84 optimizer.load_state_dict(self.optimizer_state)
TypeError: __init__() got an unexpected keyword argument 'num_workers'
```
But it's defined here,
Enviornments
Hello @AdityaSoni19031997 did you install from pip? If so, this feature is not yet available. The feature is only available currently if you work on the master branch, which you could install like this:
!pip install --upgrade git+https://github.com/zalandoresearch/flair.git
Yep I installed from pip!
Thanks for the info guys, will pull the master branch :)
On Wed, 29 May 2019, 01:01 Alan Akbik, notifications@github.com wrote:
Hello @AdityaSoni19031997 https://github.com/AdityaSoni19031997 did you
install from pip? If so, this feature is not yet available. The feature is
only available currently if you work on the master branch, which you could
install like this:!pip install --upgrade git+https://github.com/zalandoresearch/flair.git
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Most helpful comment
Hello @AdityaSoni19031997 did you install from pip? If so, this feature is not yet available. The feature is only available currently if you work on the master branch, which you could install like this: