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import os
from collections import defaultdict
from typing import List
import datasets
from datasets import Sequence, Value, load_dataset
from .process import process_text, get_structured_data
from typing import List
from math import ceil
from .configs import SUB_DATASETS
def processing(data, name):
if name == "processed":
data['text'] = [process_text(text) for text in data['text']]
elif name == "structured":
data['text'] = [process_text(text) for text in data['text']]
data['structured_text'] = [
get_structured_data(text, default_value={"item": [], "content": []}) for text in data['text']
]
return data
def sliding(texts: List[str], window_size: int=5, stride:int=3) -> List[str]:
n_iter = ceil((len(texts)-window_size)/stride)+1
return [texts[i*stride:i*stride+window_size] for i in range(n_iter)]
class NamuWiki(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = SUB_DATASETS
def _info(self):
return datasets.DatasetInfo(
description="",
features=self.config.features,
homepage=self.config.url,
citation=self.config.citation + "\n" + "",
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
if self.config.name == "processed":
data_file = dl_manager.download(self.config.data_url)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": data_file,
"split": "train"
}
),
]
elif self.config.name.startswith(("char", "word")):
_, length = self.config.name.split("-")
length = int(length)
data_file = dl_manager.download(self.config.data_url)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": data_file,
"split": "train",
"length": length
}
),
]
elif self.config.name == "raw":
data_file = dl_manager.download_and_extract(self.config.data_url)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": os.path.join(data_file, "namuwiki_20210301.json"),
"split": "train"
}
),
]
def _generate_examples(self, data_file, split, length=None):
os.system("pip install ijson")
import ijson
"""Generate NamuWiki examples."""
_TARGET = {"title", "text", "contributors.item"}
n, output = 0, defaultdict(list)
with open(data_file) as f:
for key, dtype, value in ijson.parse(f):
key = key.replace("item.", "")
if key == "namespace" and len(output):
output = {k: (v[0] if k != "contributors" else v) for k, v in output.items()}
yield n, processing(output, self.config.name)
output = defaultdict(list)
n += 1
elif key in _TARGET:
output[key.replace(".item", "")].append(value)
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