torch.nn.utils.rnn.pad_sequence
torch.nn.utils.rnn.pad_sequence(sequences, batch_first=False, padding_value=0.0)
Pad a list of variable length Tensors with "padding_value"
"pad_sequence" stacks a list of Tensors along a new dimension, and
   pads them to equal length. For example, if the input is list of
   sequences with size "L x " and if batch_first is False, and "T x B
   x " otherwise.
B is batch size. It is equal to the number of elements in
   "sequences". T is length of the longest sequence. L is length
   of the sequence. *** is any number of trailing dimensions,
   including none.
-[ Example ]-



from torch.nn.utils.rnn import pad_sequence
a = torch.ones(25, 300)
b = torch.ones(22, 300)
c = torch.ones(15, 300)
pad_sequence([a, b, c]).size()
   torch.Size([25, 3, 300])



Note:
 This function returns a Tensor of size "T x B x *" or "B x T x *"
