I’m training a PyTorch model on data stored in Google BigQuery (basically a SQL like database). What’s the best way to fetch data in batches for training a model such that I don’t bottleneck the training process. Querying too many times is slow and the dataset is way too large to fit into memory. Any best practices here or existing tools for this?