Convert dataset to Parquet (#1)

- Convert dataset to Parquet (f8ab564145f59424eed0f9117eb20d29e1839309)
- Add 'icliniq' config data files (1cb9cb918123701e6e7ac5cfb7f913e163d85535)
- Delete loading script (65ce16d82c2625da03055b66091456704070dc52)
- Delete data file (e7887c450e4ef5e9161b1a5b2719560f67492081)
- Delete data file (76e2999cd25d2d1a4158f389949ac757c6ee862a)
- Delete data file (b6a11cbe175a175470e7f01fc67900e73c1130d5)
- Delete data file (c1ae78c971b7c432c5ccb27d67626af568209f1f)
- Delete data file (5e04be9e740914e46d87cef315baa4c8fd251dee)
- Delete data file (5c7d04610f73e38107d97471cc6e7ac962a8acc5)

README.md

@@ -0,0 +1,60 @@
+---
+dataset_info:
+- config_name: healthcaremagic
+  features:
+  - name: tgt
+    dtype: string
+  - name: src
+    dtype: string
+  - name: id
+    dtype: int64
+  splits:
+  - name: train
+    num_bytes: 190539493
+    num_examples: 181122
+  - name: validation
+    num_bytes: 23782271
+    num_examples: 22641
+  - name: test
+    num_bytes: 23813362
+    num_examples: 22642
+  download_size: 147248621
+  dataset_size: 238135126
+- config_name: icliniq
+  features:
+  - name: tgt
+    dtype: string
+  - name: src
+    dtype: string
+  - name: id
+    dtype: int64
+  splits:
+  - name: train
+    num_bytes: 30971422
+    num_examples: 24851
+  - name: validation
+    num_bytes: 3819950
+    num_examples: 3105
+  - name: test
+    num_bytes: 3831220
+    num_examples: 3108
+  download_size: 15177985
+  dataset_size: 38622592
+configs:
+- config_name: healthcaremagic
+  data_files:
+  - split: train
+    path: healthcaremagic/train-*
+  - split: validation
+    path: healthcaremagic/validation-*
+  - split: test
+    path: healthcaremagic/test-*
+- config_name: icliniq
+  data_files:
+  - split: train
+    path: icliniq/train-*
+  - split: validation
+    path: icliniq/validation-*
+  - split: test
+    path: icliniq/test-*
+---

healthcaremagic/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:496f41974e7b3b02cb249578d84cef6471e97cd2f146f5a2c6448b86f8d5bf0b
+size 14726476

healthcaremagic/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c841e4195c48d124d34ebd3cc70adbdb9f0bc5c33b3fe98e1be9358120899a8d
+size 117821940

healthcaremagic/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af00dd230260ad01be236897c2e629937e46cce5c728e35ce09a634e59c5a17c
+size 14700205

icliniq/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5beaa488cd06e327165037113805f5c2deb1873b8827fc8e76560bc6633be27f
+size 1495322

icliniq/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c60e46419585e618b5180d1506dabc33f8b681371fc73135be99830387c69323
+size 12180652

icliniq/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4d9daa583a88f6498490f8857b5abb0d84008a130c8ea352f0fdb8087603cd51
+size 1502011

med_dialog.py

@@ -1,148 +0,0 @@
-import datasets
-import os
-import json
-
-
-_CITATION = """
-    @article{chen2020meddiag,
-      title={MedDialog: a large-scale medical dialogue dataset},
-      author={Chen, Shu and Ju, Zeqian and Dong, Xiangyu and Fang, Hongchao and Wang, Sicheng and Yang, Yue and Zeng,
-              Jiaqi and Zhang, Ruisi and Zhang, Ruoyu and Zhou, Meng and Zhu, Penghui and Xie, Pengtao},
-      journal={arXiv preprint arXiv:2004.03329},
-      year={2020}
-    }
-"""
-
-_DESCRIPTION = """
-    "The MedDialog dataset (English) contains conversations between doctors and patients.
-    It has 0.26 million dialogues. The data is continuously growing and more dialogues will be added.
-    The raw dialogues are from healthcaremagic.com and icliniq.com. All copyrights of the data belong
-    to healthcaremagic.com and icliniq.com."
-
-    The following is an example from the healthcaremagic.com subset:
-
-    Patient: I get cramps on top of my left forearm and hand and it causes my hand and fingers to draw up and it
-    hurts. It mainly does this when I bend my arm. I ve been told that I have a slight pinch in a nerve in my neck.
-    Could this be a cause? I don t think so. Doctor: Hi there. It may sound difficult to believe it ,but the nerves
-    which supply your forearms and hand, start at the level of spinal cord and on their way towards the forearm and
-    hand regions which they supply, the course of these nerves pass through difference fascial and muscular planes
-    that can make them susceptible to entrapment neuropathies. Its a group of conditions where a nerve gets
-    compressed between a muscle and a bone, or between the fibers of a muscle that it pierces or passes through.
-    Also, the compression can happen when the nerves are travelling around a blood vessel which can mechanically put
-    pressure on them. Usually patients who would be having such a problem present with a dull aching pain over the
-    arm and forearm. If it is not too severe and does not cause any neurological deficits then conservative management
-    with Pregabalin and Vitamin B complex tablets, activity modifications and physiotherapy can be started which
-    will provide relief. Avoid the activities which exaggerate your problem.
-
-    Could painful forearms be related to pinched nerve in neck?
-
-
-    The following is an example from the icliniq.com subset:
-
-    Patient: Hello doctor,  We are looking for a second opinion on my friend's MRI scan of both the knee joints as he
-    is experiencing excruciating pain just above the patella. He has a sudden onset of severe pain on both the knee
-    joints about two weeks ago. Previously he had a similar episode about two to three months ago and it subsided
-    after resting and painkillers. Doctor: Hi. I viewed the right and left knee MRI images. (attachment removed to
-    protect patient identity).  Left knee: The MRI, left knee joint shows a complex tear in the posterior horn of the
-    medial meniscus area and mild left knee joint effusion. There is some fluid between the semimembranous and medial
-    head of gastrocnemius muscles. There is a small area of focal cartilage defect in the upper pole of the patella
-    with mild edematous fat. The anterior and posterior cruciate ligaments are normal. The medial and lateral
-    collateral ligaments are normal. Right knee: The right knee joint shows mild increased signal intensity in the
-    posterior horn of the medial meniscus area and minimal knee joint effusion. There is minimal fluid in the back
-    of the lower thigh and not significant. There is a suspicious strain in the left anterior cruciate ligament
-    interiorly but largely the attachments are normal. The posterior cruciate ligament is normal. There are subtle
-    changes in the upper pole area of the right patella and mild edema. There is mild edema around the bilateral
-    distal quadriceps tendons, but there is no obvious tear of the tendons.
-
-    My friend has excruciating knee pain. Please interpret his MRI report
-
-
-    Paper: https://arxiv.org/abs/2004.03329
-    Code: https://github.com/UCSD-AI4H/Medical-Dialogue-System
-
-    @article{chen2020meddiag,
-      title={MedDialog: a large-scale medical dialogue dataset},
-      author={Chen, Shu and Ju, Zeqian and Dong, Xiangyu and Fang, Hongchao and Wang, Sicheng and Yang, Yue and Zeng,
-              Jiaqi and Zhang, Ruisi and Zhang, Ruoyu and Zhou, Meng and Zhu, Penghui and Xie, Pengtao},
-      journal={arXiv preprint arXiv:2004.03329},
-      year={2020}
-    }
-
-    We used the data preprocessing from "BioBART: Pretraining and Evaluation o A Biomedical Generative Language Model"
-    (Yuan et al.) and generated the following splits:
-
-    |Dataset         | Train      | Valid   | Test   |
-    |--------------- |------------|---------|--------|
-    |HealthCareMagic | 181,122    | 22,641  | 22,642 |
-    |iCliniq         | 24,851     | 3,105   | 3,108  |
-
-    Yuan et al. described, "HealthCareMagic's summaries are more abstractive and are written in a formal style,
-    unlike iCliniq's patient-written summaries."
-
-    Paper: https://arxiv.org/abs/2204.03905
-    Code: https://github.com/GanjinZero/BioBART
-
-    @misc{https://doi.org/10.48550/arxiv.2204.03905,
-      doi = {10.48550/ARXIV.2204.03905},
-      url = {https://arxiv.org/abs/2204.03905},
-      author = {Yuan, Hongyi and Yuan, Zheng and Gan, Ruyi and Zhang, Jiaxing and Xie, Yutao and Yu, Sheng},
-      keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences,
-                  FOS: Computer and information sciences},
-      title = {BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model},
-      publisher = {arXiv},
-      year = {2022},
-      copyright = {arXiv.org perpetual, non-exclusive license}
-    }
-"""
-
-class MedDialog(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description=_DESCRIPTION)
-            for name in ["healthcaremagic", "icliniq"]
-        ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "tgt": datasets.Value("string"),
-                "src": datasets.Value("string"),
-                "id": datasets.Value("int64"),
-
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage="",
-            license="",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        train_json = dl_manager.download(os.path.join(self.config.name, "train.json"))
-        valid_json = dl_manager.download(os.path.join(self.config.name, "valid.json"))
-        test_json = dl_manager.download(os.path.join(self.config.name, "test.json"))
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"path": train_json},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"path": valid_json},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"path": test_json},
-            )
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, path):
-        with open(path, encoding="utf-8") as f:
-            file = json.load(f)
-            for key, row in enumerate(file["data"]):
-                yield key, row