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DuConv/duconv-dev.parquet

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DuConv/duconv-test_1.parquet

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DuConv/duconv-test_2.parquet

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DuConv/duconv-train.parquet

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README.md

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----
-license: apache-2.0
----

duconv.py

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-# coding=utf-8
-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-# Copyright 2020 The TensorFlow Datasets Authors and the 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
-
-import json
-import os
-
-import datasets
-from datasets.tasks import QuestionAnsweringExtractive
-
-logger = datasets.logging.get_logger(__name__)
-
-_DESCRIPTION = """\
-Duconv is a chinese conversation \
-dataset, designed to evaluate the dialogue models.
-"""
-
-_URL = "https://bj.bcebos.com/paddlenlp/datasets/DuConv.zip"
-
-
-class DuconvConfig(datasets.BuilderConfig):
-    """BuilderConfig for Duconv."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for Duconv.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(DuconvConfig, self).__init__(**kwargs)
-
-
-class Duconv(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        DuconvConfig(
-            name="DuConv",
-            version=datasets.Version("1.0.0", ""),
-            description=_DESCRIPTION,
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({
-                "id":
-                datasets.Value("string"),
-                "goal":
-                datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
-                "knowledge":
-                datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
-                "conversation":
-                datasets.Sequence(datasets.Value("string")),
-                "history":
-                datasets.Sequence(datasets.Value("string")),
-                "response":
-                datasets.Value("string"),
-            }),
-            # No default supervised_keys (as we have to pass both question
-            # and context as input).
-            supervised_keys=None,
-            homepage="https://arxiv.org/pdf/1906.05572.pdf",
-        )
-
-    def _split_generators(self, dl_manager):
-        dl_dir = dl_manager.download_and_extract(_URL)
-
-        return [
-            datasets.SplitGenerator(name="train",
-                                    gen_kwargs={
-                                        "filepath":
-                                        os.path.join(dl_dir, 'DuConv',
-                                                     'train.txt'),
-                                    }),
-            datasets.SplitGenerator(name="dev",
-                                    gen_kwargs={
-                                        "filepath":
-                                        os.path.join(dl_dir, 'DuConv',
-                                                     'dev.txt'),
-                                    }),
-            datasets.SplitGenerator(name="test_1",
-                                    gen_kwargs={
-                                        "filepath":
-                                        os.path.join(dl_dir, 'DuConv',
-                                                     'test_1.txt'),
-                                    }),
-            datasets.SplitGenerator(name="test_2",
-                                    gen_kwargs={
-                                        "filepath":
-                                        os.path.join(dl_dir, 'DuConv',
-                                                     'test_2.txt'),
-                                    }),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        key = 0
-        with open(filepath, 'r', encoding="utf-8") as fin:
-            for line in fin:
-                duconv = json.loads(line)
-
-                goal = duconv["goal"] if "goal" in duconv.keys() else [[]]
-                knowledge = duconv["knowledge"] if "knowledge" in duconv.keys(
-                ) else [[]]
-                conversation = duconv[
-                    "conversation"] if "conversation" in duconv.keys() else []
-                history = duconv["history"] if "history" in duconv.keys(
-                ) else []
-                response = duconv["response"] if "response" in duconv.keys(
-                ) else ""
-
-                yield key, {
-                    "id": str(key),
-                    "goal": goal,
-                    "knowledge": knowledge,
-                    "conversation": conversation,
-                    "history": history,
-                    "response": response,
-                }
-                key += 1