allow Tacotron2 decoding batch_size 1 examples (#2156)

Summary:
it seems to me that the current Tacotron2 model does not allow for decoding batch size 1 examples:
e.g. following code fails. I may have a fix for that.

```python
if __name__ == "__main__":
    max_length = 400
    n_batch = 1
    hdim = 32
    dec = _Decoder(
        encoder_embedding_dim=hdim,
        n_mels = hdim,
        n_frames_per_step = 1,
        decoder_rnn_dim = 1024,
        decoder_max_step = 2000,
        decoder_dropout = 0.1,
        decoder_early_stopping = True,
        attention_rnn_dim = 1024,
        attention_hidden_dim = 128,
        attention_location_n_filter = 32,
        attention_location_kernel_size = 31,
        attention_dropout = 0.1,
        prenet_dim = 256,
        gate_threshold = 0.5)

    inp = torch.rand((n_batch, max_length, hdim))
    lengths = torch.tensor([max_length]).expand(n_batch).to(inp.device, inp.dtype)
    dec(inp, torch.rand((n_batch, hdim, max_length)), lengths)[0]
    dec.infer(inp, lengths)[0]
```

Pull Request resolved: https://github.com/pytorch/audio/pull/2156

Reviewed By: carolineechen

Differential Revision: D33744006

Pulled By: nateanl

fbshipit-source-id: 7d04726dfe7e45951ab0007f22f10f90f26379a7

torchaudio/models/tacotron2.py

@@ -749,7 +749,7 @@ class _Decoder(nn.Module):
             )
 
             mel_outputs += [mel_output.squeeze(1)]
-            gate_outputs += [gate_output.squeeze()]
+            gate_outputs += [gate_output.squeeze(1)]
             alignments += [attention_weights]
 
         mel_specgram, gate_outputs, alignments = self._parse_decoder_outputs(