Consider the following Python code snippet:
```python
from transformers import RagTokenizer, RagRetriever, RagTokenForGeneration
tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-base")
retriever = RagRetriever.from_pretrained("facebook/rag-token-base")
generator = RagTokenForGeneration.from_pretrained("facebook/rag-token-base")
query = "What is the capital of France?"
context = "France is a country located in Western Europe. Its capital is Paris."
input_dict = tokenizer.prepare_seq2seq_batch(query, return_tensors="pt")
generated = generator.generate(input_ids=input_dict['input_ids'])
print(tokenizer.decode(generated[0], skip_special_tokens=True))
```
What is the purpose of the `tokenizer.prepare_seq2seq_batch()` method in this code?
a. To prepare the input query for the sequence-to-sequence generation model by tokenizing the query and converting it into the appropriate tensor format.
b. To preprocess the retrieved passages for the RAGRetriever
