# coding=utf-8

# Lint as: python3
"""mindgames datasets"""

from __future__ import absolute_import, division, print_function

import json
import os
import textwrap
import six
import datasets


CITATION = r"""
@article{sileo2023mindgames,
  title={MindGames: Targeting Theory of Mind in Large Language Models with Dynamic Epistemic Modal Logic},
  author={Sileo, Damien and Lernould, Antoine},
  journal={arXiv preprint arXiv:2305.03353},
  year={2023}
}
"""

DESCRIPTION = """\
mindgames json tasks
"""

DATA_URL = "https://www.dropbox.com/s/yamo3jsgzdhkim8/mindgames.zip?dl=1"

CONFIGS=['internal','forehead','forehead-mirror','explicit']

class mindgames_Config(datasets.BuilderConfig):
    """BuilderConfig for mindgames."""

    def __init__(
        self,
        text_features,
        label_classes=None,
        **kwargs,
    ):
        """BuilderConfig for mindgames.
        Args:
          text_features: `dict[string, string]`, map from the name of the feature
            dict for each text field to the name of the column in the tsv file
          data_url: `string`, url to download the zip file from
          data_dir: `string`, the path to the folder containing the tsv files in the
            downloaded zip
          citation: `string`, citation for the data set
          url: `string`, url for information about the data set
        """

        super(mindgames_Config, self).__init__(
            version=datasets.Version("1.0.0", ""), **kwargs
        )

        self.text_features = text_features
        self.data_url = DATA_URL
        self.data_dir = self.name#os.path.join("", self.name)
        self.citation = textwrap.dedent(CITATION)
        self.description = ""


class mindgames(datasets.GeneratorBasedBuilder):

    """The General Language Understanding Evaluation (mindgames) benchmark."""

    BUILDER_CONFIG_CLASS = mindgames_Config

    BUILDER_CONFIGS = [
        mindgames_Config(
            name=name,
            text_features={"inputs": "inputs"},
        ) for name in CONFIGS
    ]

    def _info(self):

        #features["idx"] = datasets.Value("int32")
        return datasets.DatasetInfo(
            description=DESCRIPTION,
            #features=datasets.Features(features),
            citation=self.config.citation + "\n" + CITATION,
        )

    def _split_generators(self, dl_manager):
        data_dir = dl_manager.download_and_extract(self.config.data_url)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "data_file": f"{data_dir}/train-{self.config.name}.jsonl",
                    "split": "train",
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "data_file": f"{data_dir}/validation-{self.config.name}.jsonl",
                    "split": "test",
                },
            ),           
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "data_file": f"{data_dir}/test-{self.config.name}.jsonl",
                    "split": "validation",
                },
            ),
        ]

    def _generate_examples(self, data_file,split):
        """Yields examples."""
        with open(data_file, "r", encoding="utf-8") as f:
            for id_, line in enumerate(f):
                line_dict = json.loads(line)
                yield id_, line_dict