File size: 4,207 Bytes
e1603e9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
# coding=utf-8
import datasets
logger = datasets.logging.get_logger(__name__)
_URL = "https://huggingface.co/datasets/adalbertojunior/punctuation-ptbr/resolve/main/"
_TRAIN_FILE = "train.txt"
_TEST_FILE = "test.txt"
_DEV_FILE = "dev.txt"
class Punctuation(datasets.GeneratorBasedBuilder):
"""Punctuation dataset."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name='punctuation-ptbr', version=VERSION, description="punctuation-ptbr 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=[
"O",
"B-Virgula",
"B-Ponto",
"B-Interrogacao",
]
)
),
}
),
supervised_keys=None,
)
def _split_generators(self, dl_manager):
#
urls_to_download = {
"train": f"{_URL}{_TRAIN_FILE}",
"dev": f"{_URL}{_DEV_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,
}
|