"""Global state of the app.
"""

import re

from transformers import AutoConfig
import torch
from nnsight import LanguageModel

conf = AutoConfig.from_pretrained("yp-edu/gpt2-stockfish-debug")
model = LanguageModel("yp-edu/gpt2-stockfish-debug")
model.eval()


def make_prompt(fen):
    board, player, castling, *fen_remaining = fen.split()
    board = re.sub(r"(\d)", lambda m: "0" * int(m.group(1)), board)
    spaced_board = " ".join(board)
    spaced_castling = " ".join(castling)
    full_fen = f"{spaced_board} {player} {spaced_castling} {' '.join(fen_remaining)}"
    return f"FEN: {full_fen} \nMOVE:"


def model_cache(fen):
    global model
    prompt = f"FEN: {fen}\nMOVE:"
    attentions = {i: [] for i in range(12)}
    with model.generate(prompt, max_new_tokens=10, output_attentions=True) as tracer:
        out = model.generator.output.save()
        for i in range(10):
            for i in range(12):
                attentions[i].append(model.transformer.h[i].attn.output[2].save())
            tracer.next()
    real_attentions = {}
    for i in range(12):
        real_attentions[i] = []
        for a in attentions[i]:
            try:
                _ = a.shape
                real_attentions[i].append(a)
            except ValueError:
                break
    return out, real_attentions


def attribute_seqence(fen, out, attn_tensor):
    global model

    out_str = model.tokenizer.batch_decode(out)[0]