Expected more than 1 value per channel when training

I am following the instructions to fit the model. However, I am getting this error: ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 50])

How to resolve this? What does this mean?

from contextualized_topic_models.models.ctm import CTM
from contextualized_topic_models.utils.data_preparation import TextHandler
from contextualized_topic_models.utils.data_preparation import bert_embeddings_from_file
from contextualized_topic_models.datasets.dataset import CTMDataset

handler = TextHandler("topic_tst.txt")
handler.prepare() # create vocabulary and training data

training_bert = bert_embeddings_from_file("topic_tst.txt", "./roberta-large-nli-mean-tokens")


training_dataset = CTMDataset(handler.bow, training_bert, handler.idx2token)

ctm = CTM(input_size=len(handler.vocab), bert_input_size=1024, inference_type="combined", n_components=50)

ctm.fit(training_dataset) # run the model

[vinid]

Yay! That’s great!

I’m closing the issue then 😃

[rajevv]

Update: Add other lines in the file does solve the problem. Thanks!