from typing import List, Optional, Union

import torch

from transformers import CLIPTokenizer, CLIPTextModel


class PromptProcessor():
    def __init__(self, tokenizer: CLIPTokenizer, text_encoder: CLIPTextModel):
        self.tokenizer = tokenizer
        self.text_encoder = text_encoder

    def get_input_ids(self, prompt: Union[str, List[str]]):
        return self.tokenizer(
            prompt,
            padding="do_not_pad",
        ).input_ids

    def unify_input_ids(self, input_ids: List[int]):
        return self.tokenizer.pad(
            {"input_ids": input_ids},
            padding=True,
            pad_to_multiple_of=self.tokenizer.model_max_length,
            return_tensors="pt"
        ).input_ids

    def get_embeddings(self, input_ids: torch.IntTensor):
        prompts = input_ids.shape[0]
        input_ids = input_ids.reshape((-1, self.tokenizer.model_max_length)).to(self.text_encoder.device)
        text_embeddings = self.text_encoder(input_ids)[0].reshape((prompts, -1, 768))
        return text_embeddings