Qwen Image prompt encoding is not padding to max seq len

### Describe the bug

The pipeline method for QwenImagePipeline.encode_prompts is not padding correctly; it's padding by the longest sequence length in the batch, which leaves very very short embeds that are out of distribution for the models' training set.

The padding should remain at 1024 tokens even after the system prompt is dropped. The attention mask has to be expanded too.

### Reproduction

Execute `QwenImagePipeline.encode_prompts()` and check resulting shape.

### Logs

```shell
prompt_embeds.shape=torch.Size([1, 1024, 3584]), prompt_embeds_mask.shape=torch.Size([1, 1024])

^ after fixing.

prompt_embeds.shape=torch.Size([1, 5, 3584]) prompt_embeds_mask.shape=torch.Size([1, 5])

^ before.
```
prompt was simply `minecraft`

this leads to extremely high loss at training time unless very-long prompts are used.

at inference time, it causes patch embed artifacts because the RoPE is not accustomed to these positions.

### System Info

Latest git main.

### Who can help?

_No response_