diff --git a/utils/sequence_batch_generator.py b/utils/sequence_batch_generator.py
index 524e58b..005caf3 100644
--- a/utils/sequence_batch_generator.py
+++ b/utils/sequence_batch_generator.py
@@ -125,10 +125,9 @@ class SequenceGenerator(BatchGenerator):
                 first_label.append(
                     self.label[sequence_index][start_index: start_index + self.sequence_size])
         if self.pipeline is not None:
-            for sequence_index, (data_sequence, label_sequence) in enumerate(zip(first_data, first_label)):
-                for data_index, (data_sample, label_sample) in enumerate(zip(data_sequence, label_sequence)):
-                    first_data[sequence_index][data_index], first_label[sequence_index][data_index] = self.pipeline(
-                        data_sample, label_sample)
+            for batch_index, (data_sequence, label_sequence) in enumerate(zip(first_data, first_label)):
+                first_data[batch_index], first_label[batch_index] = self.pipeline(
+                    np.asarray(data_sequence), np.asarray(label_sequence))
         first_data = np.asarray(first_data)
         first_label = np.asarray(first_label)
         self.batch_data = first_data
@@ -181,8 +180,9 @@ class SequenceGenerator(BatchGenerator):
             for sequence_index, start_index in self.index_list[
                     self.step * self.batch_size:(self.step + 1) * self.batch_size]:
                 data.append(
-                    [self.data_processor(input_data)
-                        for input_data in self.data[sequence_index][start_index: start_index + self.sequence_size]])
+                    np.asarray(
+                        [self.data_processor(input_data)
+                         for input_data in self.data[sequence_index][start_index: start_index + self.sequence_size]]))
         else:
             data = []
             for sequence_index, start_index in self.index_list[
@@ -195,8 +195,9 @@ class SequenceGenerator(BatchGenerator):
             for sequence_index, start_index in self.index_list[
                     self.step * self.batch_size:(self.step + 1) * self.batch_size]:
                 label.append(
-                    [self.label_processor(input_data)
-                     for input_data in self.label[sequence_index][start_index: start_index + self.sequence_size]])
+                    np.asarray(
+                        [self.label_processor(input_data)
+                         for input_data in self.label[sequence_index][start_index: start_index + self.sequence_size]]))
         else:
             label = []
             for sequence_index, start_index in self.index_list[
@@ -205,12 +206,10 @@ class SequenceGenerator(BatchGenerator):
 
         # Process through pipeline
         if self.pipeline is not None:
-            for sequence_index in range(len(data)):
-                for data_index in range(len(data[sequence_index])):
-                    piped_data, piped_label = self.pipeline(
-                        data[sequence_index][data_index], label[sequence_index][data_index])
-                    self.cache_data[self.current_cache][data_index] = piped_data
-                    self.cache_label[self.current_cache][data_index] = piped_label
+            for batch_index in range(len(data)):
+                piped_data, piped_label = self.pipeline(data[batch_index], label[batch_index])
+                self.cache_data[self.current_cache][batch_index] = piped_data
+                self.cache_label[self.current_cache][batch_index] = piped_label
         else:
             self.cache_data[self.current_cache][:len(data)] = np.asarray(data)
             self.cache_label[self.current_cache][:len(label)] = np.asarray(label)
@@ -221,17 +220,22 @@ if __name__ == '__main__':
         data = np.array(
             [[1, 2, 3, 4, 5, 6, 7, 8, 9], [11, 12, 13, 14, 15, 16, 17, 18, 19]], dtype=np.uint8)
         label = np.array(
-            [[.1, .2, .3, .4, .5, .6, .7, .8, .9], [.11, .12, .13, .14, .15, .16, .17, .18, .19]], dtype=np.uint8)
+            [[10, 20, 30, 40, 50, 60, 70, 80, 90], [110, 120, 130, 140, 150, 160, 170, 180, 190]], dtype=np.uint8)
 
-        for data_processor in [None, lambda x:x]:
-            for prefetch in [False, True]:
-                for num_workers in [1, 2]:
-                    print(f'{data_processor=} {prefetch=} {num_workers=}')
-                    with SequenceGenerator(data, label, 5, 2, data_processor=data_processor,
-                                           prefetch=prefetch, num_workers=num_workers) as batch_generator:
-                        for _ in range(9):
-                            print(batch_generator.batch_data, batch_generator.epoch, batch_generator.step)
-                            batch_generator.next_batch()
-                    print()
+        def pipeline(data, label):
+            return data, label
+
+        for pipeline in [None, pipeline]:
+            for data_processor in [None, lambda x:x]:
+                for prefetch in [False, True]:
+                    for num_workers in [1, 2]:
+                        print(f'{pipeline=} {data_processor=} {prefetch=} {num_workers=}')
+                        with SequenceGenerator(data, label, 5, 2, data_processor=data_processor, pipeline=pipeline,
+                                               prefetch=prefetch, num_workers=num_workers) as batch_generator:
+                            for _ in range(9):
+                                print(batch_generator.batch_data.tolist(), batch_generator.batch_label.tolist(),
+                                      batch_generator.epoch, batch_generator.step)
+                                batch_generator.next_batch()
+                        print()
 
     test()