import pytorch_lightning as pl
import torch

from model.light_module import LightModule
from model.modeling_wit import ModelRunner
from model.tokenization_qwen import QWenTokenizer
import numpy as np

import configuration
import dataset.dataset as ds
import dataset.node_tree as nt

if __name__ == "__main__":

    checkpoint_path = "log/bigger/version_1/checkpoints/epoch=14-step=74040.ckpt"

    qwen = LightModule.load_from_checkpoint(checkpoint_path=checkpoint_path)
    qwen.eval()
    conf = qwen.config
    torch.manual_seed(conf.seed)
    np.random.seed(conf.seed)

    train_dataloader, val_dataloader = ds.InitDataset(conf)

    loader = train_dataloader.dataset

    map = loader.meaning_dataset.get_meaning_map()
    seqs = {}
    for batch in loader:
        for m in batch["meaning"]:
            seqs[m] = map.get_sequence(m)
    while True:
        m = int(input("input meaning: "))
        total = 0
        for seq in seqs.values():
            total = total + seq.count(m)
        print(f"meaning of {m} count as {total}")