Clean up

fashion_mnist_label_drift.py

@@ -16,10 +16,8 @@
 """IMDb movie revies dataset mixed with Trip Advisor Hotel Reviews to simulate drift accross time."""
 
 
-import pickle
-import os
-import pandas as pd
 import datasets
+import pickle
 
 
 
@@ -130,7 +128,6 @@ class FashionMNISTLabelDrift(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         extracted_paths = dl_manager.download_and_extract(_URLS)
-        print("EXTRACTED PATHS=",extracted_paths)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split("training"),
@@ -160,7 +157,6 @@ class FashionMNISTLabelDrift(datasets.GeneratorBasedBuilder):
     def _generate_examples(self, filepath):
         # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        print("FILEPATH=",filepath)
         with open(filepath, 'rb') as pkl_file:
             data = pickle.load(pkl_file, encoding='bytes')
             prediction_ts=data['prediction_ts']