added padding function

teng_ml/util/pad.py

@@ -0,0 +1,14 @@
+import torch
+import torch.nn.utils.rnn as rnn
+import numpy as np
+
+class PadSequences:
+    def __call__(self, batch):
+        # batch = [(data, label)]
+        # sort by length
+        sorted_batch = sorted(batch, key=lambda sample: sample[0].shape[0], reverse=True)
+        sequences = [torch.Tensor(sample[0]) for sample in sorted_batch]
+        labels = torch.Tensor(np.array([sample[1] for sample in sorted_batch]))
+        lengths = torch.IntTensor(np.array([seq.shape[0] for seq in sequences]))
+        sequences_padded = rnn.pad_sequence(sequences, batch_first=True)
+        return sequences_padded, lengths, labels