wip

fashion_mnist_label_drift.py

@@ -159,7 +159,7 @@ 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("CACA = ", filepath)
         with open(filepath) as file:
             df = pd.read_hdf(file)
             print(len(df))
@@ -178,21 +178,21 @@ class FashionMNISTLabelDrift(datasets.GeneratorBasedBuilder):
 #                    "ner_tags":ner_tags_list,
 #                }
 #
-    #def _generate_examples(self, filepath, split):
-    #    """This function returns the examples in the raw form."""
-    #    # Images
-    #    with open(filepath[0], "rb") as f:
-    #        # First 16 bytes contain some metadata
-    #        _ = f.read(4)
-    #        size = struct.unpack(">I", f.read(4))[0]
-    #        _ = f.read(8)
-    #        images = np.frombuffer(f.read(), dtype=np.uint8).reshape(size, 28, 28)
-
-    #    # Labels
-    #    with open(filepath[1], "rb") as f:
-    #        # First 8 bytes contain some metadata
-    #        _ = f.read(8)
-    #        labels = np.frombuffer(f.read(), dtype=np.uint8)
-
-    #    for idx in range(size):
-    #        yield idx, {"image": images[idx], "label": int(labels[idx])}
+    def _generate_examples(self, filepath, split):
+        """This function returns the examples in the raw form."""
+        # Images
+        with open(filepath[0], "rb") as f:
+            # First 16 bytes contain some metadata
+            _ = f.read(4)
+            size = struct.unpack(">I", f.read(4))[0]
+            _ = f.read(8)
+            images = np.frombuffer(f.read(), dtype=np.uint8).reshape(size, 28, 28)
+
+        # Labels
+        with open(filepath[1], "rb") as f:
+            # First 8 bytes contain some metadata
+            _ = f.read(8)
+            labels = np.frombuffer(f.read(), dtype=np.uint8)
+
+        for idx in range(size):
+            yield idx, {"image": images[idx], "label": int(labels[idx])}