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# coding=utf-8
# Copyright 2020 HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Lint as: python3
"""Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition"""
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@inproceedings{BV-Custom-Invoice-Data,
title = "Invoice Data Shared Task: Language-Independent Named Entity Recognition",
author = "BureauVeritas",
}
"""
_DESCRIPTION = """\
Custom Invoice Dataset
"""
_URL = "dataset.tar.gz"
class InvoiceDataConfig(datasets.BuilderConfig):
"""BuilderConfig for Conll2003"""
def __init__(self, **kwargs):
"""BuilderConfig forConll2003.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(InvoiceDataConfig, self).__init__(**kwargs)
class Conll2003(datasets.GeneratorBasedBuilder):
"""Conll2003 dataset."""
BUILDER_CONFIGS = [
InvoiceDataConfig(name="InvoiceData", version=datasets.Version("1.0.0"), description="InvoiceDataConfig dataset"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"tokens": datasets.Sequence(datasets.Value("string")),
"ner_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"O",
"B-LOC",
"I-LOC",
"B-PROD",
"I-PROD",
"B-MODEL_YEAR",
"I-MODEL_YEAR",
"B-BRAND",
"I-BRAND",
"B-MODEL",
"I-MODEL",
"B-STATE",
"I-STATE",
"B-PRICE",
"I-PRICE",
"B-CHAR",
"I-CHAR",
]
)
),
}
),
supervised_keys=None,
homepage="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
path = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(path, 'dataset.jsonl')})
]
def _generate_examples(self, filepath):
logger.info("⏳ Generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
guid = 0
tokens = []
ner_tags = []
for line in f:
import json
print(json.loads(line))
obj = json.loads(line)
yield guid, obj
guid += 1
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