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raise ValueError("Could not parse hparam %s in %s" % (name, values))
ValueError: Could not parse hparam shared_embedding_and_softmax_weights in batch_size=15000,device_list=[0,1],update_cycle=2,train_steps=2000000,keep_checkpoint_max=5,shared_embedding_and_softmax_weights=True,shared_source_target_embedding=True
The text was updated successfully, but these errors were encountered:
In the above example, you should set shared_embedding_and_softmax=true instead of shared_embedding_and_softmax=True. The document of PyTorch implementation will be uploaded soon. We have tested our implementation on several datasets, but we do not observe inf loss problem.
Some commands for additional parameters are not working in the pytorch version, so, do you have an pytorch-oriented manual?
For example:
--parameters=batch_size=15000,device_list=[0,1],update_cycle=2,train_steps=2000000,keep_checkpoint_max=5,shared_embedding_and_softmax_weights=True,shared_source_target_embedding=True
raise ValueError("Could not parse hparam %s in %s" % (name, values))
ValueError: Could not parse hparam shared_embedding_and_softmax_weights in batch_size=15000,device_list=[0,1],update_cycle=2,train_steps=2000000,keep_checkpoint_max=5,shared_embedding_and_softmax_weights=True,shared_source_target_embedding=True
The text was updated successfully, but these errors were encountered: