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dataset_infos.json

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+{
+  "testaunic23": {
+    "description": "test testaunic23",
+    "citation": "test testaunic23",
+    "homepage": "",
+    "license": "",
+    "features": {
+      "id": { "dtype": "string", "id": null, "_type": "Value" },
+      "tokens": {
+        "feature": { "dtype": "string", "id": null, "_type": "Value" },
+        "length": -1,
+        "id": null,
+        "_type": "Sequence"
+      },
+      "pos_tags": {
+        "feature": {
+          "num_classes": 47,
+          "names": [
+            "\"",
+            "''",
+            "#",
+            "$",
+            "(",
+            ")",
+            ",",
+            ".",
+            ":",
+            "``",
+            "CC",
+            "CD",
+            "DT",
+            "EX",
+            "FW",
+            "IN",
+            "JJ",
+            "JJR",
+            "JJS",
+            "LS",
+            "MD",
+            "NN",
+            "NNP",
+            "NNPS",
+            "NNS",
+            "NN|SYM",
+            "PDT",
+            "POS",
+            "PRP",
+            "PRP$",
+            "RB",
+            "RBR",
+            "RBS",
+            "RP",
+            "SYM",
+            "TO",
+            "UH",
+            "VB",
+            "VBD",
+            "VBG",
+            "VBN",
+            "VBP",
+            "VBZ",
+            "WDT",
+            "WP",
+            "WP$",
+            "WRB"
+          ],
+          "names_file": null,
+          "id": null,
+          "_type": "ClassLabel"
+        },
+        "length": -1,
+        "id": null,
+        "_type": "Sequence"
+      },
+      "ner_tags": {
+        "feature": {
+          "num_classes": 11,
+          "names": [
+            "O",
+            "B-ENTITY",
+            "I-ENTITY",
+            "B-SYSTEM",
+            "I-SYSTEM",
+            "B-DOCUMENT",
+            "I-DOCUMENT",
+            "B-ORG",
+            "I-ORG",
+            "B-LOC",
+            "I-LOC"
+          ],
+          "names_file": null,
+          "id": null,
+          "_type": "ClassLabel"
+        },
+        "length": -1,
+        "id": null,
+        "_type": "Sequence"
+      }
+    },
+    "post_processed": null,
+    "supervised_keys": null,
+    "builder_name": "testaunic23",
+    "config_name": "testaunic23",
+    "version": {
+      "version_str": "1.0.0",
+      "description": null,
+      "major": 1,
+      "minor": 0,
+      "patch": 0
+    },
+    "splits": {
+      "train": {
+        "name": "train",
+        "num_examples": 249,
+        "dataset_name": "testaunic23"
+      },
+      "validation": {
+        "name": "validation",
+        "num_examples": 32,
+        "dataset_name": "testaunic23"
+      },
+      "test": {
+        "name": "test",
+        "num_examples": 32,
+        "dataset_name": "testaunic23"
+      }
+    }
+  }
+}

testaunic23.py

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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
+"""test testaunic23"""
+
+import logging
+
+import datasets
+
+
+_CITATION = """\
+test testaunic23
+"""
+
+_DESCRIPTION = """\
+test testaunic23
+"""
+
+_URL = "https://github.com/andreyokamura-unicamp/test_dataset/"
+_TRAINING_FILE = "train.txt"
+_DEV_FILE = "dev.txt"
+_TEST_FILE = "test.txt"
+
+
+class testaunic23Config(datasets.BuilderConfig):
+    """BuilderConfig for testaunic23"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for testaunic23.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(testaunic23Config, self).__init__(**kwargs)
+
+
+class testaunic23(datasets.GeneratorBasedBuilder):
+    """testaunic23 dataset."""
+
+    BUILDER_CONFIGS = [
+        testaunic23Config(name="testaunic23", version=datasets.Version("1.0.0"), description="testaunic23 dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "document_id": datasets.Value("int32"),
+                    "sentence_id": datasets.Value("int32"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "chunk_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-ADJP",
+                                "I-ADJP",
+                                "B-ADVP",
+                                "I-ADVP",
+                                "B-CONJP",
+                                "I-CONJP",
+                                "B-INTJ",
+                                "I-INTJ",
+                                "B-LST",
+                                "I-LST",
+                                "B-NP",
+                                "I-NP",
+                                "B-PP",
+                                "I-PP",
+                                "B-PRT",
+                                "I-PRT",
+                                "B-SBAR",
+                                "I-SBAR",
+                                "B-UCP",
+                                "I-UCP",
+                                "B-VP",
+                                "I-VP",
+                            ]
+                        )
+                    ),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-ENTITY",
+                                "I-ENTITY",
+                                "B-SYSTEM",
+                                "I-SYSTEM",
+                                "B-DOCUMENT",
+                                "I-DOCUMENT",
+                                "B-ORG",
+                                "I-ORG",
+                                "B-LOC",
+                                "I-LOC"
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAINING_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"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            document_id = 0
+            sentence_id = 0
+            tokens = []
+            pos_tags = []
+            chunk_tags = []
+            ner_tags = []
+            for line in f:
+                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
+                    if line.startswith("-DOCSTART-"):
+                        document_id += 1
+                        sentence_id = 0
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "document_id": document_id,
+                            "sentence_id": sentence_id,
+                            "tokens": tokens,
+                            "pos_tags": pos_tags,
+                            "chunk_tags": chunk_tags,
+                            "ner_tags": ner_tags,
+                        }
+                        sentence_id += 1
+                        guid += 1
+                        tokens = []
+                        pos_tags = []
+                        chunk_tags = []
+                        ner_tags = []
+                else:
+                    # conll2003 tokens are space separated
+                    splits = line.split(" ")
+                    tokens.append(splits[0])
+                    pos_tags.append(splits[1])
+                    chunk_tags.append(splits[2])
+                    ner_tags.append(splits[3].rstrip())
+            # last example
+            if tokens:
+                yield guid, {
+                    "id": str(guid),
+                    "document_id": document_id,
+                    "sentence_id": sentence_id,
+                    "tokens": tokens,
+                    "pos_tags": pos_tags,
+                    "chunk_tags": chunk_tags,
+                    "ner_tags": ner_tags,
+                }