def build_bert_decoder(model_config, checkpoint):
    """build text decoder the same as the multimodal encoder.

    Args:
        model_config (dict): model config.
        pretrain (bool): Whether to do pretrain or finetuning.
        checkpoint (bool): whether to do gradient_checkpointing.

    Returns: TODO

    """
    bert_config = BertConfig.from_json_file(model_config.text_encoder.config)
    bert_config.encoder_width = model_config.vision_encoder.get.d_model if model_config.vision_encoder.get('d_model', 0) else model_config.vision_encoder.embed_dim
    bert_config.gradient_checkpointing = checkpoint

    bert_config.fusion_layer = 0
    bert_config.num_hidden_layers = (
        bert_config.num_hidden_layers - model_config.text_encoder.fusion_layer
    )

    text_decoder, loading_info = BertLMHeadModel.from_pretrained(
        model_config.text_encoder.pretrained,
        config=bert_config,
        output_loading_info=True,
        local_files_only=True
        
    )

    return text_decoder
build text decoder the same as the multimodal encoder.

Args:
model_config (dict): model config.
pretrain (bool): Whether to do pretrain or finetuning.
checkpoint (bool): whether to do gradient_checkpointing.

Returns: TODO
videomamba/video_mm/models/backbones/bert/builder.py