You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Currently most of the integration tests such as APIs are disabled during CI because the model takes more than 4 GB to run and Travis is unable to fulfill the memory requirements.
Hence, when the PyTorch model is implemented, a small reference model needs to be prepared for integration tests.
The text was updated successfully, but these errors were encountered:
Agree with your assessment that a small reference model is needed with unit / integration tests. That will be helpful for others to assess whether to adopt it or not.
@kylase Maybe ability to load a model without any embedding layer altogether. This way all the code flow can be checked however it might require a lot of effort to make all functionality to work without one hot to embedding conversion operation including train and test input. The other way is to check with a dummy model with Vocab = 10 and rest all assigned as one . The latter should be easier to do.
Currently most of the integration tests such as APIs are disabled during CI because the model takes more than 4 GB to run and Travis is unable to fulfill the memory requirements.
Hence, when the PyTorch model is implemented, a small reference model needs to be prepared for integration tests.
The text was updated successfully, but these errors were encountered: