cannot use scheduler for grad_factor

In my model implementation, I would like to freeze the transformer (using `roberta-base` in a Tok2VecTransformer.v1) for the first 2 epochs during training. From [this spacy documentation](https://spacy.io/usage/embeddings-transformers#training-custom-model), it seems like it should be possible to set the `grad_factor` to 0 in order to disable gradients from one of the listeners. Setting this up per epoch should then be possible, according to the same documentation, by using a [scheduler](https://thinc.ai/docs/api-schedules#constant_then). In my config, I have specified the `constant_then` scheduler followed by another `constant` scheduler in the following way:
```
[components.seq2labels.model.tok2vec]
@architectures = "spacy-transformers.Tok2VecTransformer.v1"
name = "roberta-base"
tokenizer_config = {"use_fast": true}

[components.seq2labels.model.tok2vec.grad_factor]
@schedules = "constant_then.v1"
rate = 0.0
steps = 2000

[components.seq2labels.model.tok2vec.grad_factor.schedule]
@schedules = "constant.v1"
rate = 1.0
```

When initializing, I get the following error:
```
=========================== Initializing pipeline ===========================
✘ Config validation error
seq2labels.model.tok2vec -> grad_factor value is not a valid float

```
It seems to me that the scheduler may be returning and iterator instead of a float that can be used as a value here. Have I overlooked some aspect that should still be implemented/ammended?

Otherwise, if this scheduler does not work with `grad_factor`, is there another way to freeze the transformer only for the first 2 epochs of training?

Thanks for any help in advance :)