# This file is modified from https://github.com/haotian-liu/LLaVA/

import os

import torch
from transformers import PretrainedConfig, PreTrainedModel

from .base_projector import MultimodalProjector, MultimodalProjectorConfig


def build_mm_projector(model_type_or_path: str, config: PretrainedConfig) -> PreTrainedModel:
    if model_type_or_path is None:
        return None

    ## load from pretrained model
    if config.resume_path:
        assert os.path.exists(model_type_or_path), f"Resume mm projector path {model_type_or_path} does not exist!"
        return MultimodalProjector.from_pretrained(model_type_or_path, config, torch_dtype=eval(config.model_dtype))
    ## build from scratch
    else:
        mm_projector_cfg = MultimodalProjectorConfig(model_type_or_path)
        mm_projector = MultimodalProjector(mm_projector_cfg, config).to(eval(config.model_dtype))
        return mm_projector