I am using the fast-ai library in order to train a sample of the IMDB reviews dataset. I want to use it for sentiment analysis and I have trained the model in a VM by using this tutorial.
I saved the data_lm and data_clas models, then the encoder ft_enc and after that I saved the classifier learner sentiment_model. I, then, got those 4 files from the VM and put them in my machine and wanted to use those pretrained models in order to classify sentiment.
This is what I did:
# Use the IMDB_SAMPLE file
path = untar_data(URLs.IMDB_SAMPLE)
# Language model data
data_lm = TextLMDataBunch.from_csv(path, 'texts.csv')
# Sentiment classifier model data
data_clas = TextClasDataBunch.from_csv(path, 'texts.csv',
vocab=data_lm.train_ds.vocab, bs=32)
# Build a classifier using the tuned encoder (tuned in the VM)
learn = text_classifier_learner(data_clas, AWD_LSTM, drop_mult=0.5)
learn.load_encoder('ft_enc')
# Load the trained model
learn.load('sentiment_model')
After that, I wanted to use that model in order to predict the sentiment of a sentence. When executing this code, I ran into the following error:
RuntimeError: Error(s) in loading state_dict for AWD_LSTM:
size mismatch for encoder.weight: copying a param with shape torch.Size([8731, 400]) from checkpoint, the shape in current model is torch.Size([8888, 400]).
size mismatch for encoder_dp.emb.weight: copying a param with shape torch.Size([8731, 400]) from checkpoint, the shape in current model is torch.Size([8888, 400]).
And the Traceback is:
Traceback (most recent call last):
File "C:/Users/user/PycharmProjects/SentAn/mainApp.py", line 51, in <module>
learn = load_models()
File "C:/Users/user/PycharmProjects/SentAn/mainApp.py", line 32, in load_models
learn.load_encoder('ft_enc')
File "C:\Users\user\Desktop\py_code\env\lib\site-packages\fastai\text\learner.py", line 68, in load_encoder
encoder.load_state_dict(torch.load(self.path/self.model_dir/f'{name}.pth'))
File "C:\Users\user\Desktop\py_code\env\lib\site-packages\torch\nn\modules\module.py", line 769, in load_state_dict
self.__class__.__name__, "\n\t".join(error_msgs)))
So the error occurs when loading the encoder. But, I also tried to remove the load_encoder line but the same error occurred at the next line learn.load('sentiment_model').
I searched through the fast-ai forum and noticed that others also had this issue but found no solution. In this post the user says that this might have to do with different preprocessing, though I couldnāt understand why this would happen.
Could anyone please help me with that issue. I have tried many different things but I cannot find something to get past this. Any help would be appreciated.
Has anyone else come up with any solutions to this problem?
