max_length = text_input.input_ids.shape[-1]
uncond_input = tokenizer(
    [""] * batch_size, padding="max_length", max_length=max_length, return_tensors="pt"
)
uncond_embeddings = text_encoder(uncond_input.input_ids.to(torch_device))[0]