Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
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+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- expert-generated
+- found
+languages:
+  en:
+  - en
+  zh:
+  - zh
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+  en:
+  - n<1K
+  zh:
+  - 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- question-answering
+task_ids:
+- closed-domain-qa
+---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** https://github.com/UCSD-AI4H/COVID-Dialogue
+- **Repository:** The data is also present in the same [GIT](https://github.com/UCSD-AI4H/COVID-Dialogue) repository
+- **Paper:** https://pengtaoxie.github.io/coviddiag.pdf
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+COVID-Dialogue-Dataset-English is an English medical dialogue dataset about COVID-19 and other types of pneumonia. Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice. There are 603 consultations.
+
+COVID-Dialogue-Dataset-Chinese is a Chinese medical dialogue dataset about COVID-19 and other types of pneumonia. Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice. There are 1393 consultations.
+
+The dataset is present as a single text file. COVID-Dialogue-Dataset-Chinese.txt for Chinese and COVID-Dialogue-Dataset-English.txt for English.
+
+### Supported Tasks and Leaderboards
+
+Used for QA tasks. There is also a COVID-19 dialogue generation model available for the Chinese Data. The pre-print and more information is available in [this arxiv pre-print](https://arxiv.org/abs/2005.05442).
+
+### Languages
+
+Monolingual. The datasets are in English (EN) and Chinese (ZH)
+
+## Dataset Structure
+
+### Data Instances
+
+An example of dialogue is:
+
+```
+{
+	'dialogue_id': 602, 
+	'dialogue_url': 'https://www.healthtap.com/member/fg?page=/search/covid', 
+	'dialogue_turns': [{'speaker': 'Patient', 
+			    'utterance': 'Can coronavirus symptoms be mild for some people versus severe? For example, could it just involve being very fatigued, low grade fever for a few days and not the extreme symptoms? Or is it always a full blown cold and struggle to breathe?Can coronavirus symptoms be mild for some people versus severe? For example, could it just involve being very fatigued, low grade fever for a few days and not the extreme symptoms? Or is it always a full blown cold and struggle to breathe?'}, 
+                           {'speaker': 'Doctor', 
+                            'utterance': 'In brief:   Symptoms vary.   Some may have no symptoms at all. Some can be life threatening.   Would you like to video or text chat with me?'}]
+}
+```
+
+The dataset is built from [icliniq.com](https://www.icliniq.com/), [healthcaremagic.com](https://www.healthcaremagic.com/), [healthtap.com](https://www.healthtap.com/) and all copyrights of the data belong to these websites. _(for English)_
+
+The dataset is built from [Haodf.com](https://www.haodf.com/) and all copyrights of the data belong to [Haodf.com](https://www.haodf.com/).  _(for Chinese)_
+
+### Data Fields
+
+Each consultation consists of the below:
+- ID
+- URL
+- Description of patient’s medical condition
+- Dialogue
+- Diagnosis and suggestions (Optional, mostly for Chinese)
+
+For generating the QA only the below fields have been considered:
+- ID : Consultatation Identifier (restarts for each file)
+- URL: The url link of the extracted conversation
+- Dialogue : The conversation between the doctor and the patient.
+
+These are arranged as below in the prepared dataset. Each item will be represented with these parameters.
+
+- "file_name": string - signifies the file from which the conversation was extracted
+- "dialogue_id": int32 - the dialogue id
+- "dialogue_url": string - url of the conversation
+- "dialogue_turns": datasets.Sequence - sequence of dialogues between patient and the doctor.Consists ClassLabel(names=["病人", "医生"]), and "utterance"(string) for each turn. (ClassLable(names=["Patient", "Doctor"]) for english)
+
+### Data Splits
+
+There are no data splits on the original data
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+@article{ju2020CovidDialog,
+  title={CovidDialog: Medical Dialogue Datasets about COVID-19},
+  author={Ju, Zeqian and Chakravorty, Subrato and He, Xuehai and Chen, Shu and Yang, Xingyi and Xie, Pengtao},
+  journal={ https://github.com/UCSD-AI4H/COVID-Dialogue}, 
+  year={2020}
+}

covid_qa_ucsd.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""Covid Dialog dataset in English and Chinese"""
+
+from __future__ import absolute_import, division, print_function
+
+import copy
+import os
+import re
+import textwrap
+
+import datasets
+
+
+# BibTeX citation
+_CITATION = """\
+@article{ju2020CovidDialog,
+  title={CovidDialog: Medical Dialogue Datasets about COVID-19},
+  author={Ju, Zeqian and Chakravorty, Subrato and He, Xuehai and Chen, Shu and Yang, Xingyi and Xie, Pengtao},
+  journal={ https://github.com/UCSD-AI4H/COVID-Dialogue},
+  year={2020}
+}
+"""
+
+# Official description of the dataset
+_DESCRIPTION = textwrap.dedent(
+    """
+    COVID-Dialogue-Dataset is amedical dialogue dataset about COVID-19 and other types of pneumonia.
+    Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice.
+    There are 603 consultations in English and 1393 consultations in Chinese.
+    """
+)
+
+# Link to an official homepage for the dataset here
+_HOMEPAGE = "https://github.com/UCSD-AI4H/COVID-Dialogue"
+
+_LICENSE = ""
+_CHINESE_QA = "COVID-Dialogue-Dataset-Chinese.txt"
+_ENGLISH_QA = "COVID-Dialogue-Dataset-English.txt"
+
+
+class CovidQaUcsd(datasets.GeneratorBasedBuilder):
+    """Dataset has one file having consulatations purely based on COVID queries"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="en", version=VERSION, description="The dataset of medical dialogs related to Covid in English."
+        ),
+        datasets.BuilderConfig(
+            name="zh", version=VERSION, description="The dataset of medical dialogs related to Covid in Chinese."
+        ),
+    ]
+
+    @property
+    def manual_download_instructions(self):
+        return """\
+                \nBoth the English and Chinese text files are present in https://github.com/UCSD-AI4H/COVID-Dialogue.
+                It is present as COVID-Dialogue-Dataset-English.txt (for the english dialogues) and COVID-Dialogue-Dataset-Chinese.txt
+                (for the Chinese Dialog).
+
+                To load the dataset, simple pass the folder where the file is saved to the 'data_dir' param in the datasets.load_dataset(...) option.
+                The data directory can e.g. be "/Downloads/".
+                The data can then be loaded using the below command:\n
+                `datasets.load_dataset("covid_qa_ucsd", name="en", data_dir="/Downloads/")`.
+
+                Just change the 'name' parameter to 'zh' for Chinese.
+                TAKE CARE NOT TO CHANGE THE NAME OF THE INPUT FILE
+        """
+
+    def _info(self):
+        # This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
+        if self.config.name == "zh":  # For english dialouge data
+            features = datasets.Features(
+                {
+                    "dialogue_id": datasets.Value("int32"),
+                    "dialogue_url": datasets.Value("string"),
+                    "dialogue_turns": datasets.Sequence(
+                        {
+                            "speaker": datasets.ClassLabel(names=["病人", "医生"]),
+                            "utterance": datasets.Value("string"),
+                        }
+                    ),
+                }
+            )
+
+        if self.config.name == "en":  # For english dialouge data
+            features = datasets.Features(
+                {
+                    "dialogue_id": datasets.Value("int32"),
+                    "dialogue_url": datasets.Value("string"),
+                    "dialogue_turns": datasets.Sequence(
+                        {
+                            "speaker": datasets.ClassLabel(names=["Patient", "Doctor"]),
+                            "utterance": datasets.Value("string"),
+                        }
+                    ),
+                }
+            )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        if self.config.name == "zh":
+            path_to_manual_file = os.path.join(os.path.abspath(os.path.expanduser(dl_manager.manual_dir)), _CHINESE_QA)
+        if self.config.name == "en":
+            path_to_manual_file = os.path.join(os.path.abspath(os.path.expanduser(dl_manager.manual_dir)), _ENGLISH_QA)
+
+        if not os.path.exists(path_to_manual_file):
+            raise FileNotFoundError(
+                "{} does not exist. Make sure the file is present in the directory specified in the data_dir specified in the input {} `datasets.load_dataset('covid_qa_ucsd', 'en', data_dir=...)`. Manual download instructions: {})".format(
+                    path_to_manual_file, dl_manager.manual_dir, self.manual_download_instructions
+                )
+            )
+
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": path_to_manual_file})]
+
+    def _generate_examples(self, filepath):
+        """Yields examples. Iterates over the file and creates appropriate dialogue data
+
+        NOTE:
+        - The code makes some assumption on the structure of the raw .txt file.
+        - There are some checks to separate different id's. Hopefully, should not cause further issues later when more txt files are added.
+        """
+        data_lang = self.config.name
+        id_ = -1
+        with open(filepath, encoding="utf-8") as f_in:
+            # Parameters to just "sectionize" the raw data
+            last_part = ""
+            last_dialog = {}
+            last_list = []
+            last_user = ""
+            check_list = []
+
+            # These flags are present to have a single function address both chinese and english data
+            # English data is a little hahazard (i.e. the sentences spans multiple different lines),
+            # Chinese is compact with one line for doctor and patient.
+            conv_flag = False
+            des_flag = False
+
+            while True:
+                line = f_in.readline()
+                if not line:
+                    break
+
+                # Extracting the dialog id
+                if line[:2] == "id":  # Hardcode alert!
+                    # Handling ID references that may come in the description
+                    # These were observed in the Chinese dataset and were not
+                    # followed by numbers
+                    try:
+                        dialogue_id = int(re.findall(r"\d+", line)[0])
+                    except IndexError:
+                        continue
+
+                # Extracting the url
+                if line[:4] == "http":  # Hardcode alert!
+                    dialogue_url = line.rstrip()
+
+                # Extracting the patient info from description.
+                if line[:11] == "Description":  # Hardcode alert!
+                    last_part = "description"
+                    last_dialog = {}
+                    last_list = []
+                    last_user = ""
+                    last_conv = {"speaker": "", "utterance": ""}
+                    while True:
+                        line = f_in.readline()
+                        if (not line) or (line in ["\n", "\n\r"]):
+                            break
+                        else:
+                            if data_lang == "zh":  # Condition in chinese
+                                if line[:5] == "病情描述：":  # Hardcode alert!
+                                    last_user = "病人"
+                                    sen = line[6:].rstrip()
+                                    des_flag = True
+
+                            if data_lang == "en":
+                                last_user = "Patient"
+                                sen = line.rstrip()
+                                des_flag = True
+
+                            if des_flag:
+                                if sen == "":
+                                    continue
+                                if sen in check_list:
+                                    last_conv["speaker"] = ""
+                                    last_conv["utterance"] = ""
+                                else:
+                                    last_conv["speaker"] = last_user
+                                    last_conv["utterance"] = sen
+                                    check_list.append(sen)
+                                des_flag = False
+                                break
+
+                # Extracting the conversation info from dialogue.
+                elif line[:8] == "Dialogue":  # Hardcode alert!
+                    if last_part == "description" and len(last_conv["utterance"]) > 0:
+                        last_part = "dialogue"
+                        if data_lang == "zh":
+                            last_user = "病人"
+
+                        if data_lang == "en":
+                            last_user = "Patient"
+
+                        while True:
+                            line = f_in.readline()
+                            if (not line) or (line in ["\n", "\n\r"]):
+                                conv_flag = False
+                                last_user = ""
+                                last_list.append(copy.deepcopy(last_conv))
+                                # To ensure close of conversation, only even number of sentences
+                                # are extracted
+                                last_turn = len(last_list)
+                                if int(last_turn / 2) > 0:
+                                    temp = int(last_turn / 2)
+                                    id_ += 1
+                                    last_dialog["dialogue_id"] = dialogue_id
+                                    last_dialog["dialogue_url"] = dialogue_url
+                                    last_dialog["dialogue_turns"] = last_list[: temp * 2]
+                                    yield id_, last_dialog
+                                break
+
+                            if data_lang == "zh":
+                                if line[:3] == "病人：" or line[:3] == "医生：":  # Hardcode alert!
+                                    user = line[:2]  # Hardcode alert!
+                                    line = f_in.readline()
+                                    conv_flag = True
+
+                            # The elif block is to ensure that multi-line sentences are captured.
+                            # This has been observed only in english.
+                            if data_lang == "en":
+                                if line.strip() == "Patient:" or line.strip() == "Doctor:":  # Hardcode alert!
+                                    user = line.replace(":", "").rstrip()
+                                    line = f_in.readline()
+                                    conv_flag = True
+                                elif line[:2] != "id":  # Hardcode alert!
+                                    conv_flag = True
+
+                            # Continues till the next ID is parsed
+                            if conv_flag:
+                                sen = line.rstrip()
+                                if sen == "":
+                                    continue
+
+                                if user == last_user:
+                                    last_conv["utterance"] = last_conv["utterance"] + sen
+                                else:
+                                    last_user = user
+                                    last_list.append(copy.deepcopy(last_conv))
+                                    last_conv["utterance"] = sen
+                                    last_conv["speaker"] = user

dataset_infos.json

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+{"en": {"description": "\nCOVID-Dialogue-Dataset is amedical dialogue dataset about COVID-19 and other types of pneumonia.\nPatients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice.\nThere are 603 consultations in English and 1393 consultations in Chinese.\n", "citation": "@article{ju2020CovidDialog,\n  title={CovidDialog: Medical Dialogue Datasets about COVID-19},\n  author={Ju, Zeqian and Chakravorty, Subrato and He, Xuehai and Chen, Shu and Yang, Xingyi and Xie, Pengtao},\n  journal={ https://github.com/UCSD-AI4H/COVID-Dialogue},\n  year={2020}\n}\n", "homepage": "https://github.com/UCSD-AI4H/COVID-Dialogue", "license": "", "features": {"dialogue_id": {"dtype": "int32", "id": null, "_type": "Value"}, "dialogue_url": {"dtype": "string", "id": null, "_type": "Value"}, "dialogue_turns": {"feature": {"speaker": {"num_classes": 2, "names": ["Patient", "Doctor"], "names_file": null, "id": null, "_type": "ClassLabel"}, "utterance": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "covid_qa_ucsd", "config_name": "en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 484944, "num_examples": 572, "dataset_name": "covid_qa_ucsd"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 484944, "size_in_bytes": 484944}, "zh": {"description": "\nCOVID-Dialogue-Dataset is amedical dialogue dataset about COVID-19 and other types of pneumonia.\nPatients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice.\nThere are 603 consultations in English and 1393 consultations in Chinese.\n", "citation": "@article{ju2020CovidDialog,\n  title={CovidDialog: Medical Dialogue Datasets about COVID-19},\n  author={Ju, Zeqian and Chakravorty, Subrato and He, Xuehai and Chen, Shu and Yang, Xingyi and Xie, Pengtao},\n  journal={ https://github.com/UCSD-AI4H/COVID-Dialogue},\n  year={2020}\n}\n", "homepage": "https://github.com/UCSD-AI4H/COVID-Dialogue", "license": "", "features": {"dialogue_id": {"dtype": "int32", "id": null, "_type": "Value"}, "dialogue_url": {"dtype": "string", "id": null, "_type": "Value"}, "dialogue_turns": {"feature": {"speaker": {"num_classes": 2, "names": ["\u75c5\u4eba", "\u533b\u751f"], "names_file": null, "id": null, "_type": "ClassLabel"}, "utterance": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "covid_qa_ucsd", "config_name": "zh", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1352377, "num_examples": 1088, "dataset_name": "covid_qa_ucsd"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 1352377, "size_in_bytes": 1352377}}

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