#!/usr/bin/env python3
#

import random
import sys, os, pdb
import json, math
import datasets
from datasets import load_dataset
import csv

random.seed(42)

DATASETS = {
    "natural_language_understanding": [
                        "ATIS", "ATIS-NER", "BANKING77", "BANKING77-OOS", "CLINC-Single-Domain-OOS-banking", 
                        "CLINC-Single-Domain-OOS-credit_cards", "CLINC150", "DSTC8-SGD", "HWU64", "MIT-Movie",
                        "MIT-Restaurant", "RESTAURANTS8K", "SNIPS", "SNIPS-NER", "TOP", "TOP-NER"
                    ],  
    "task_oriented": [
                        "ABCD", "AirDialogue", "BiTOD", "CaSiNo", "CraigslistBargains", 
                        "Disambiguation", "DSTC2-Clean", "FRAMES", "GECOR", "HDSA-Dialog", 
                        "KETOD", "KVRET", "MetaLWOZ", "MS-DC", "MuDoCo", 
                        "MulDoGO", "MultiWOZ_2.1", "MULTIWOZ2_2", "SGD", "SimJointGEN", 
                        "SimJointMovie", "SimJointRestaurant", "STAR", "Taskmaster1", "Taskmaster2", 
                        "Taskmaster3", "WOZ2_0"
                    ],
    "dialogue_summarization": [
                        "AMI", "CRD3", "DialogSum", "ECTSum", "ICSI", 
                        "MediaSum", "QMSum", "SAMSum", "TweetSumm", "ConvoSumm", 
                        "SummScreen_ForeverDreaming", "SummScreen_TVMegaSite"
                    ],
    "conversational_recommendation": [
                        "Redial", "DuRecDial-2.0", "OpenDialKG", "SalesBot",
                    ],
    "open_domain": [
                        "chitchat-dataset", "ConvAI2", "AntiScam", "Empathetic", "HH-RLHF", 
                        "PLACES3.5", "Prosocial", "SODA"
                    ],
    "knowledge_grounded": [
                        "CompWebQ", "CoQA", "CoSQL", "DART", "FeTaQA", 
                        "GrailQA", "HybridQA", "MTOP", "MultiModalQA", "SParC", 
                        "Spider", "SQA", "ToTTo", "WebQSP", "WikiSQL", 
                        "WikiTQ", "wizard_of_internet", "wizard_of_wikipedia"
                    ],
}

class Test(object):
    def __init__(self):
        pass

    def test_single_dataset(self, data_name):
        # dataset = load_dataset("Salesforce/dialogstudio", data_name, revision="download")
        dataset = load_dataset("Salesforce/dialogstudio", data_name, revision="download")
        dataset_size = {
            "train":0,
            "validation":  0,
            "test": 0,
        }
        for split in dataset:
            dataset_size[split] = len(dataset[split])
        print(dataset_size)
        # pdb.set_trace()
        return dataset_size

    def test_all(self):
        with open("dataset_stats.csv", "w", newline="") as tf: 
            writer = csv.writer(tf)
            writer.writerow(["Category", "Data_name", "train", "val", "test"])
            for cat, dataset_list in DATASETS.items():
                for data_name in dataset_list:
                    dataset_size = self.test_single_dataset(data_name=data_name)
                    writer.writerow([cat, data_name] + list(dataset_size.values()))


def main():
    test = Test()
    # test.test_all()
    # test.test_single_dataset("WOZ2_0")
    # test.test_single_dataset("MULTIWOZ2_2")
    # test.test_single_dataset("Taskmaster1")
    test.test_single_dataset("Taskmaster2")

if __name__ == "__main__":
    main()