Load Data in CSV Format¶

1. .load is a general method for reading data in different format. You have to specify the format of the data via the method .format of course. .csv (both for CSV and TSV), .json and .parquet are specializations of .load. .format is optional if you use a specific loading function (csv, json, etc.).

1. If your data can be fit into the CPU memory, it is a good practice to save your data into one pickle file (or other format that you know how to deserialize). This comes with several advantages. First, it is easier and faster to read from a single big file rather than many small files. Second, it avoids the possible system error of openning too many files (even though avoiding lazying data loading is another way to fix the issue). Some example datasets (e.g., MNIST) have separate training and testing files (i.e., 2 pickle files), so that research work based on it can be easily reproduced. I personally suggest that you keep only 1 file containing all data when implementing your own Dataset class. You can always use the function torch.utils.data.random_split