invoice_data.py

# 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"
# _TRAINING_FILE = "dataset.jsonl"


# 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 InvoiceData(datasets.GeneratorBasedBuilder):
    """InvoiceData 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, {
                #     "id": str(guid),
                #     "tokens": tokens,
                #     "ner_tags": ner_tags,
                # }

                yield guid, obj
                guid += 1