LSTM model for the IMDB dataset

Training, deployment and testing code for a sentiment analysis model trained on the IMDB dataset.

Author: Leonardo Espín

Date: 4/25/2021

This repo uses a containerized workflow in Google Cloud to train the model. In a VM or cloud shell:

• Build the container by running

  docker build -t lstm .

• Test the container locally by running

  docker run lstm --job-dir=gs://$BUCKET/lstm_model/ \
      --epochs=1 \
      --max-seq-len=25
  

  this will limit the text-sequence size to 25 words, to speed up the test training

• Push the container to your container registry

  docker image tag lstm gcr.io/$MY_PROJECT/lstm
  docker push gcr.io/$MY_PROJECT/lstm

• Submit the training job to the AI Platform using the default model arguments. The configuration file requests a Tesla T4 GPU

   gcloud ai-platform jobs submit training lstm_$(date +"%Y%m%d_%H%M%S") \
     --job-dir gs://$BUCKET/lstm_model/ \
     --region $REGION \
     --master-image-uri gcr.io/$MY_PROJECT/lstm \
     --config config/config.yaml

Testing

The trained model can be tested through the test.ipynb notebook in the test folder. Tests include making predictions through a rest api using the tensorflow/serving container.