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README.md

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-# Dialog bAbI tasks data
-In this directory is the set of 6 tasks for testing end-to-end dialog systems in the restaurant domain as described in the paper "Learning End-to-End Goal-Oriented Dialog" by Bordes & Weston (http://arxiv.org/abs/1605.07683). The aim is that each task tests a unique aspect of dialog. Tasks are designed to complement the set of 20 bAbI tasks for story understanding already released with the paper "Towards AI Complete Question Answering: A Set of Prerequisite Toy Tasks" by Weston et al. (http://arxiv.org/abs/1502.05698).
-
-
-## Data
-For each task, there are 1000 dialogs for training, 1000 for development and 1000 for testing. For tasks 1-5, we also include a second test set (with suffix -OOV.txt) that contains dialogs including entities not present in training and development sets.
-
-The file format for each task is as follows:
-`ID user_utterance [tab] bot_utterances`
-
-The IDs for a given  dialog start at 1 and increase. When the IDs in a file reset back to 1 you can consider the following sentences as a new dialog. When the bot speaks two times in a row, we used the special token "<SILENCE>" to fill in for the missing user utterance.
-
-For example (for task 1):
-```
-1 hi	hello what can i help you with today
-2 can you make a restaurant reservation with italian cuisine for six people in a cheap price range	i'm on it
-3 <SILENCE>	where should it be
-4 rome please	ok let me look into some options for you
-5 <SILENCE>	api_call italian rome six cheap
-```
-
-The goal of the tasks is to predict the bot utterances, that can be sentences or API calls (sentences starting with the special token "api_call").
-
-Along with the train, dev and test sets, we also include a knowledge base file (dialog-babi-kb-all.txt) that contain all entities appearing in dialogs for tasks 1-5. We also include a file containing the candidates to select the answer from (dialog-babi-candidates.txt) for tasks 1-5, that is simply made of all the bot utterances in train, dev, test for these tasks.
-
-Task 6 is a bit different since its data comes from the Dialog State Tracking Challenge 2 (http://camdial.org/~mh521/dstc/), which we modified to convert it into the same format as the other tasks. There is no OOV test set associated with this task and the knowledge base (dialog-babi-task6-dstc2-kb.txt) is imperfect. This task has its own candidates file (dialog-babi-task6-dstc2-candidates.txt).
-
-
-## License
-This dataset is released under Creative Commons Attribution 3.0 Unported license. A copy of this license is included with the data.
-
-
-## Contact
-The author of this porting is Alessandro Suglia and he has only made available the dataset via
-Huggingface datasets.
-For more details on the dataset and baselines, see the paper "Learning End-to-End Goal-Oriented Dialog" by Antoine Bordes and Jason Weston (http://arxiv.org/abs/1605.07683). For any information, contact Antoine Bordes : abordes (at) fb (dot) com .

dialog_babi.py

@@ -1,525 +0,0 @@
-# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
-# Dataset license is specified in the folder data/LICENSE.txt
-
-# 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.
-
-import os
-from unicodedata import name
-
-import datasets
-
-_CITATION = """\
-@article{bordes2016learning,
-  title={Learning end-to-end goal-oriented dialog},
-  author={Bordes, Antoine and Boureau, Y-Lan and Weston, Jason},
-  journal={arXiv preprint arXiv:1605.07683},
-  year={2016}
-}
-"""
-
-_DESCRIPTION = """\
-This section presents the set of 6 tasks for testing end-to-end dialog systems in the restaurant domain described in the paper:
-
-Antoine Bordes, Y-Lan Boureau, Jason Weston, Learning End-to-End Goal-Oriented Dialog, arxiv:1605.07683.
-
-Each task tests a unique aspect of dialog. Tasks are designed to complement the set of 20 bAbI tasks for story understanding of the previous section.
-
-For each task, there are 1000 dialogs for training, 1000 for development and 1000 for testing. For tasks 1-5, we also include a second test set (with suffix -OOV.txt) that contains dialogs including entities not present in training and development sets.
-
-"""
-
-_HOMEPAGE = "https://research.facebook.com/downloads/babi/"
-
-_LICENSE = """
-CC License
-
-Dialog bAbI tasks data
-
-Copyright (c) 2016-present, Facebook, Inc. All rights reserved.
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-"""
-
-DIALOG_BABI_ARCHIVE_URL = "https://www.dropbox.com/s/20rgyj8rryvos9l/dialog-bAbI-tasks-1_6.zip?dl=1"
-
-
-class DialogBabi(datasets.GeneratorBasedBuilder):
-    """Facebook's dataset 'dialog-babi' for end-to-end dialogue learning."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="task1-API-calls", version=VERSION, description="Issuing API calls"),
-        datasets.BuilderConfig(name="task2-API-refine", version=VERSION, description="Updating API calls"),
-        datasets.BuilderConfig(name="task3-options", version=VERSION, description="Displaying options"),
-        datasets.BuilderConfig(name="task4-phone-address", version=VERSION, description="Providing extra information"),
-        datasets.BuilderConfig(name="task5-full-dialogs", version=VERSION, description="Conducting full dialogs"),
-        datasets.BuilderConfig(name="task6-dstc2", version=VERSION, description="2nd Dialog State Tracking Challenge (Henderson et al., 2014a)"),
-    ]
-
-    DEFAULT_CONFIG_NAME = "task1-API-calls"
-    CONFIGS_WITH_KB = ("task3-options", "task4-phone-address", "task5-full-dialogs")
-
-    def _info(self):
-        if self.config.name in self.CONFIGS_WITH_KB:
-            features = datasets.Features(
-                {
-                    "user_turns": datasets.Sequence(datasets.Value("string")),
-                    "system_turns": datasets.Sequence(datasets.Value("string")),
-                    "kb_facts": datasets.Sequence(feature={"turn_id":datasets.Value("int32"), "fact":datasets.Value("string")})
-                }
-            )
-        else:  
-            features = datasets.Features(
-                {
-                    "user_turns": datasets.Sequence(datasets.Value("string")),
-                    "system_turns": datasets.Sequence(datasets.Value("string"))
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(DIALOG_BABI_ARCHIVE_URL)
-        task_data_dir = os.path.join(data_dir, "dialog-bAbI-tasks-1_6", self.config.name)
-
-        if self.config.name == "task6-dstc2":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={
-                        "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-trn.txt"),
-                        "split": f"{self.config.name}-train",
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={
-                        "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-dev.txt"),
-                        "split": f"{self.config.name}-dev",
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={
-                        "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-tst.txt"),
-                        "split": f"{self.config.name}-test"
-                    },
-                )
-            ]
-            
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-trn.txt"),
-                    "split": f"{self.config.name}-train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-dev.txt"),
-                    "split": f"{self.config.name}-dev",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-tst.txt"),
-                    "split": f"{self.config.name}-test"
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split("TESTOOV"),
-                gen_kwargs={
-                    "filepath": os.path.join(task_data_dir, f"dialog-babi-{self.config.name}-tst-OOV.txt"),
-                    "split": f"{self.config.name}-test-OOV"
-                },
-            )
-        ]
-
-    def _generate_examples(self, filepath, split):
-        with open(filepath, encoding="utf-8") as f:
-            dialogue_rows = []
-            dialogue_id = 1
-
-            for row in f:
-                turn = row.strip()
-                if not turn:
-                    yield self._format_dialogue(dialogue_id,split, dialogue_rows)
-                    dialogue_rows.clear()
-                    dialogue_id += 1
-                else:
-                    dialogue_rows.append(turn)
-            
-            if dialogue_rows:
-                yield self._format_dialogue(dialogue_id, split, dialogue_rows)
-    
-    def _format_dialogue(self, dialogue_id, split, dialogue_rows):
-        
-        user_turns = []
-        system_turns = []
-        kb_facts = []
-
-        for turn_id, turn in enumerate(dialogue_rows):
-            if "\t" not in turn:
-                kb_facts.append({"turn_id": turn_id, "fact": turn})
-            else:
-                rest_turn, sys_turn = turn.split("\t")
-                _, user_turn = rest_turn.split(" ", 1)
-                user_turns.append(user_turn)
-                system_turns.append(sys_turn)
-
-
-        example_key = f"{split}-{dialogue_id}"
-
-        dialogue_dict = {
-            "user_turns": user_turns,
-            "system_turns": system_turns
-        }
-        
-        if self.config.name in self.CONFIGS_WITH_KB:
-            dialogue_dict["kb_facts"] = kb_facts
-        
-        return example_key, dialogue_dict
-                

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