Hi.

I’m trying to use the Transfomers class as in Transformer — PyTorch 1.10.1 documentation

I have some pair of of embeddings of 512 and 256 dims. My problem is that when doing this to a given pair:

```
transformer_model = nn.Transformer(nhead=16, num_encoder_layers=12)
a = torch.Size([512])
b = torch.Size([256])
out = transformer_model(a, b)
```

I get the following:

` IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)`

I have seen some related issues, but dont know how to fix it in this case. How could I solve this dimension problem?

When using just the encoder, I face another issue:

```
encoder_layer = nn.TransformerEncoderLayer(d_model=512, nhead=8)
transformer_encoder = nn.TransformerEncoder(encoder_layer, num_layers=6)
a = torch.Size([512])
transformer_encoder(a)
```

I get:

```
ValueError: not enough values to unpack (expected 3, got 1)
```

How should I reshape the tensor in this second case. Is something like this `v = torch.reshape(a, (1, 1, 512))`

the right approach? Also, could I directly project the output to 256 dims?

Thanks.