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| |
|
|
| 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_size = { |
| "train":0, |
| "validation": 0, |
| "test": 0, |
| } |
| for split in dataset: |
| dataset_size[split] = len(dataset[split]) |
| print(dataset_size) |
| |
| 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_single_dataset("Taskmaster2") |
|
|
| if __name__ == "__main__": |
| main() |
|
|
