Datasets:

GEM
/

squad_v2

""" Script to prepare the SQuAD2.0 data to the GEM format
    @author: AbinayaM02
"""

# Import libraries
import json
import pandas as pd
from sklearn.model_selection import train_test_split

# Function to generate gem id
def add_gem_id(data: dict, split: str) -> dict:
    """ 
    Add gem id for each of the datapoint in the dataset.
    Parameters:
    -----------
    data: dict,
        data.
    split: str,
        split of data (train, test or validation).
    Returns:
    --------
    dict
        dictionary with updated id
    """
    gem_id = -1
    generated_data = {"data": []}
    id_list =[]
    for example in data:
        title = example["title"]
        for paragraph in example["paragraphs"]:
            context = paragraph["context"]  # do not strip leading blank spaces GH-2585
            for qa in paragraph["qas"]:
                temp_dict = {}
                question = qa["question"]
                qa_id = qa["id"]
                answer_starts = [answer["answer_start"] for answer in qa["answers"]]
                answers = [answer["text"] for answer in qa["answers"]]
                # Features currently used are "context", "question", and "answers".
                # Others are extracted here for the ease of future expansions.
                gem_id += 1
                temp_dict["id"] = qa_id
                temp_dict["gem_id"] = f"gem-squad_v2-{split}-{gem_id}"
                temp_dict["title"] = title
                temp_dict["context"] = context
                temp_dict["question"] = question
                temp_dict["answers"] = {
                        "answer_start": answer_starts,
                        "text": answers,
                    }
                generated_data["data"].append(temp_dict)
    return generated_data


# Function to split data
def split_data(file_name: str, data_type: str) -> (dict, dict):
    """
    Method to split the data specific to SQuAD2.0
    Parameters:
    -----------
    file_name: str,
        name of the file.
    data_type: str,
        type of the data file.
    Returns:
    --------
    (dict, dict)
        split of data
    """
    
    if data_type == "json":
        with open(file_name, 'r') as json_file:
            data = json.load(json_file)["data"]
            json_file.close()
    
    # split the data into train and test
    # 90% train data 10% test data
    train, test = train_test_split(data, train_size=0.9, random_state = 42)
    return(train, test)

# Function to save json file
def save_json(data: dict, file_name: str):
    """
    Method to save the json file.
    Parameters:
    ----------
    data: dict,
        data to be saved in file.
    file_name: str,
        name of the file.
    Returns:
    --------
    None
    """

    # save the split
    with open(file_name, "w") as data_file:
        json.dump(data, data_file, indent = 2)
        data_file.close()


if __name__ == "__main__":
    # split the train data
    train, test = split_data("squad_data/train-v2.0.json", "json")
    
    # add gem id to train split
    train = add_gem_id(train, "train")
    # save the train split
    save_json(train, "train.json")

    # add gem id to test split
    test = add_gem_id(test, "test")
    # save the test split
    save_json(test, "test.json")
    
    # load validation data
    with open("squad_data/dev-v2.0.json", "r") as dev_file:
        validation = json.load(dev_file)["data"]
        dev_file.close()
    
    # add gem id and save valid.json
    validation = add_gem_id(validation, "validation")
    save_json(validation, "validation.json")

	""" Script to prepare the SQuAD2.0 data to the GEM format

	@author: AbinayaM02
	"""

	# Import libraries
	import json
	import pandas as pd
	from sklearn.model_selection import train_test_split

	# Function to generate gem id
	def add_gem_id(data: dict, split: str) -> dict:
	"""
	Add gem id for each of the datapoint in the dataset.

	Parameters:
	-----------
	data: dict,
	data.
	split: str,
	split of data (train, test or validation).

	Returns:
	--------
	dict
	dictionary with updated id
	"""
	gem_id = -1
	generated_data = {"data": []}
	id_list =[]
	for example in data:
	title = example["title"]
	for paragraph in example["paragraphs"]:
	context = paragraph["context"] # do not strip leading blank spaces GH-2585
	for qa in paragraph["qas"]:
	temp_dict = {}
	question = qa["question"]
	qa_id = qa["id"]
	answer_starts = [answer["answer_start"] for answer in qa["answers"]]
	answers = [answer["text"] for answer in qa["answers"]]
	# Features currently used are "context", "question", and "answers".
	# Others are extracted here for the ease of future expansions.
	gem_id += 1
	temp_dict["id"] = qa_id
	temp_dict["gem_id"] = f"gem-squad_v2-{split}-{gem_id}"
	temp_dict["title"] = title
	temp_dict["context"] = context
	temp_dict["question"] = question
	temp_dict["answers"] = {
	"answer_start": answer_starts,
	"text": answers,
	}
	generated_data["data"].append(temp_dict)
	return generated_data


	# Function to split data
	def split_data(file_name: str, data_type: str) -> (dict, dict):
	"""
	Method to split the data specific to SQuAD2.0

	Parameters:
	-----------
	file_name: str,
	name of the file.
	data_type: str,
	type of the data file.

	Returns:
	--------
	(dict, dict)
	split of data
	"""

	if data_type == "json":
	with open(file_name, 'r') as json_file:
	data = json.load(json_file)["data"]
	json_file.close()

	# split the data into train and test
	# 90% train data 10% test data
	train, test = train_test_split(data, train_size=0.9, random_state = 42)
	return(train, test)

	# Function to save json file
	def save_json(data: dict, file_name: str):
	"""
	Method to save the json file.

	Parameters:
	----------
	data: dict,
	data to be saved in file.
	file_name: str,
	name of the file.

	Returns:
	--------
	None
	"""

	# save the split
	with open(file_name, "w") as data_file:
	json.dump(data, data_file, indent = 2)
	data_file.close()


	if __name__ == "__main__":
	# split the train data
	train, test = split_data("squad_data/train-v2.0.json", "json")

	# add gem id to train split
	train = add_gem_id(train, "train")
	# save the train split
	save_json(train, "train.json")

	# add gem id to test split
	test = add_gem_id(test, "test")
	# save the test split
	save_json(test, "test.json")

	# load validation data
	with open("squad_data/dev-v2.0.json", "r") as dev_file:
	validation = json.load(dev_file)["data"]
	dev_file.close()

	# add gem id and save valid.json
	validation = add_gem_id(validation, "validation")
	save_json(validation, "validation.json")