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# coding=utf-8
import datasets
logger = datasets.logging.get_logger(__name__)
_URL = "https://huggingface.co/datasets/adalbertojunior/segmentacao_pure/resolve/main/"
_TRAIN_FILE = "split.conll"
_TEST_FILE = "test.conll"
class Harem(datasets.GeneratorBasedBuilder):
"""Harem dataset."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name='segmentacao',version=VERSION,description="segmentacao dataset"),
]
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
{
"id": datasets.Value("string"),
"tokens": datasets.Sequence(datasets.Value("string")),
"pos_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"O",
]
)
),
"chunk_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"O",
]
)
),
"ner_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"B-Segmento",
"I-Segmento",
]
)
),
}
),
supervised_keys=None,
)
def _split_generators(self, dl_manager):
#
urls_to_download = {
"train": f"{_URL}{_TRAIN_FILE}",
"dev": f"{_URL}{_TEST_FILE }",
"test": f"{_URL}{_TEST_FILE }",
}
downloaded_files = dl_manager.download_and_extract(urls_to_download)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": downloaded_files["train"], "split": "train"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepath": downloaded_files["dev"], "split": "dev"},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": downloaded_files["test"], "split": "test"},
),
]
def _generate_examples(self, filepath, split):
"""This function returns the examples in the raw (text) form by iterating on all the files."""
logger.info("⏳ Generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
guid = 0
tokens = []
pos_tags = []
chunk_tags = []
ner_tags = []
for line in f:
if line == "" or line == "\n":
if tokens:
yield guid, {
"id": str(guid),
"tokens": tokens,
"pos_tags": pos_tags,
"chunk_tags": chunk_tags,
"ner_tags": ner_tags,
}
guid += 1
tokens = []
pos_tags = []
chunk_tags = []
ner_tags = []
else:
splits = line.split(" ")
tokens.append(splits[0])
pos_tags.append(splits[1])
chunk_tags.append(splits[2])
ner_tags.append(splits[-1].rstrip())
# last example
yield guid, {
"id": str(guid),
"tokens": tokens,
"pos_tags": pos_tags,
"chunk_tags": chunk_tags,
"ner_tags": ner_tags,
} |