wip

fashion_mnist_label_drift.py

@@ -17,6 +17,7 @@
 
 
 import csv
+import pandas as pd
 import datasets
 
 
@@ -158,22 +159,25 @@ 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.
-
-        with open(filepath) as csv_file:
-            csv_reader = csv.reader(csv_file, delimiter='\t')
-            for id_, row in enumerate(csv_reader):
-                prediction_ts,language,text,ner_tags = row
-                ner_tags_list = list(ner_tags.strip('[]').split(' '))
-                tokens = text.split(":-:")
-                if id_==0:
-                    continue
-                yield id_, {
-                    "prediction_ts":prediction_ts,
-                    "language":language,
-                    "split_text": tokens,
-                    "ner_tags":ner_tags_list,
-                }
-
+        df = pd.read_hdf(filepath)
+        print(len(df))
+        print(df.columns)
+
+#        with open(filepath) as csv_file:
+#            csv_reader = csv.reader(csv_file, delimiter='\t')
+#            for id_, row in enumerate(csv_reader):
+#                prediction_ts,language,text,ner_tags = row
+#                ner_tags_list = list(ner_tags.strip('[]').split(' '))
+#                tokens = text.split(":-:")
+#                if id_==0:
+#                    continue
+#                yield id_, {
+#                    "prediction_ts":prediction_ts,
+#                    "language":language,
+#                    "split_text": tokens,
+#                    "ner_tags":ner_tags_list,
+#                }
+#
     #def _generate_examples(self, filepath, split):
     #    """This function returns the examples in the raw form."""
     #    # Images