Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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cos_e.py

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+# coding=utf-8
+# 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
+"""Commonsense Explanations (CoS-E) Dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """
+@inproceedings{rajani2019explain,
+     title = {Explain Yourself! Leveraging Language models for Commonsense Reasoning},
+    author = {Rajani, Nazneen Fatema  and
+      McCann, Bryan  and
+      Xiong, Caiming  and
+      Socher, Richard}
+      year={2019}
+    booktitle = {Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)}
+    url ={https://arxiv.org/abs/1906.02361}
+}
+"""
+
+_DESCRIPTION = """
+Common Sense Explanations (CoS-E) allows for training language models to
+automatically generate explanations that can be used during training and
+inference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.
+"""
+
+_COS_E_URL = "https://raw.githubusercontent.com/salesforce/cos-e/master/data/"
+
+# COS E has explanations for the CQA dataset, which is joined by ID.
+_CQA_V1_11_URL_TRAIN = "https://s3.amazonaws.com/commensenseqa/train_rand_split.jsonl"
+_CQA_V1_11_URL_DEV = "https://s3.amazonaws.com/commensenseqa/dev_rand_split.jsonl"
+_CQA_V1_11_URL_TEST = "https://s3.amazonaws.com/commensenseqa/test_rand_split_no_answers.jsonl"
+
+_CQA_V1_0_URL_TRAIN = os.path.join(_COS_E_URL, "v1.0/train_rand_split.jsonl")
+_CQA_V1_0_URL_DEV = os.path.join(_COS_E_URL, "v1.0/dev_rand_split.jsonl")
+_CQA_V1_0_URL_TEST = os.path.join(_COS_E_URL, "v1.0/test_rand_split_no_answers.jsonl")
+
+
+def _download_and_index_cqa(dl_manager, name):
+    """Downloads CQA and returns it, indexed by id, for joining with Cos-E."""
+
+    downloaded_files = dl_manager.download_and_extract(
+        {
+            "cqa_train": _CQA_V1_11_URL_TRAIN if name == "v1.11" else _CQA_V1_0_URL_TRAIN,
+            "cqa_dev": _CQA_V1_11_URL_DEV if name == "v1.11" else _CQA_V1_0_URL_DEV,
+            "cqa_test": _CQA_V1_11_URL_TEST if name == "v1.11" else _CQA_V1_0_URL_TEST,
+        }
+    )
+
+    # NB: "cqa_test" is included in the files, but not in any of the CoS-E splits.
+    cqa_splits = ["cqa_train", "cqa_dev"]
+    cqa_complete = []
+    for split in cqa_splits:
+        with open(downloaded_files[split], encoding="utf-8") as f:
+            for _, line in enumerate(f):
+                d = json.loads(line)
+                cqa_complete.append(d)
+
+        # Index the CQA dataset by id for joining with Cos-E.
+        cqa_indexed = {}
+    for d in cqa_complete:
+        cqa_indexed[d["id"]] = d
+    return cqa_indexed
+
+
+def _get_choices_and_answer(cqa):
+    """Returns choices and the answer from a cqa example."""
+    choices = []
+    answer_key = cqa["answerKey"]
+    answer = None
+    for choice in cqa["question"]["choices"]:
+        choices.append(choice["text"])
+        if answer_key == choice["label"]:
+            answer = choice["text"]
+    return choices, answer
+
+
+class CosEConfig(datasets.BuilderConfig):
+
+    """ BuilderConfig for CosE"""
+
+    def __init__(self, **kwargs):
+        """
+
+        Args:
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super(CosEConfig, self).__init__(**kwargs)
+
+
+class CosE(datasets.GeneratorBasedBuilder):
+    """CoS-E: Common Sense Explanations corpus."""
+
+    BUILDER_CONFIGS = [
+        CosEConfig(
+            name="v1.0",
+            description="cos-e version 1.0",
+            version=datasets.Version("1.0.0", ""),
+        ),
+        CosEConfig(
+            name="v1.11",
+            description="cos-e version 1.11",
+            version=datasets.Version("1.11.0", ""),
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "choices": datasets.features.Sequence(datasets.Value("string")),
+                    "answer": datasets.Value("string"),
+                    "abstractive_explanation": datasets.Value("string"),
+                    "extractive_explanation": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/salesforce/cos-e",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        # NB: The CQA Dataset should be read only once, and only by callers who
+        # want to _create_ the Cos-E dataset from scratch.
+        cqa_indexed = _download_and_index_cqa(dl_manager, self.config.name)
+
+        if self.config.name == "v1.11":
+            files = dl_manager.download_and_extract(
+                {
+                    "dev": [os.path.join(_COS_E_URL, "v1.11/cose_dev_v1.11_processed.jsonl")],
+                    "train": [os.path.join(_COS_E_URL, "v1.11/cose_train_v1.11_processed.jsonl")],
+                }
+            )
+
+        elif self.config.name == "v1.0":
+            files = dl_manager.download_and_extract(
+                {
+                    "dev": [os.path.join(_COS_E_URL, "v1.0/cose_dev_v1.0_processed.jsonl")],
+                    "train": [os.path.join(_COS_E_URL, "v1.0/cose_train_v1.0_processed.jsonl")],
+                }
+            )
+        else:
+            raise ValueError("Unknown config name")
+        # We use the CoS-E/CQA dev set as our validation set.
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"files": files["train"], "cqa_indexed": cqa_indexed},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"files": files["dev"], "cqa_indexed": cqa_indexed},
+            ),
+        ]
+
+    def _generate_examples(self, files, **kwargs):
+        """Yields examples."""
+        cqa_indexed = kwargs["cqa_indexed"]
+        for filepath in files:
+            with open(filepath, encoding="utf-8") as f:
+                for line in f:
+                    cos = json.loads(line)
+                    cqa = cqa_indexed[cos["id"]]
+                    choices, answer = _get_choices_and_answer(cqa)
+                    yield cos["id"], {
+                        "id": cos["id"],
+                        "question": cqa["question"]["stem"],
+                        "choices": choices,
+                        "answer": answer,
+                        "abstractive_explanation": cos["explanation"]["open-ended"],
+                        "extractive_explanation": cos["explanation"]["selected"],
+                    }

dataset_infos.json

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Leveraging Language models for Commonsense Reasoning\",\n    author = \"Rajani, Nazneen Fatema  and\n      McCann, Bryan  and\n      Xiong, Caiming  and\n      Socher, Richard\",\n      year=\"2019\",\n    booktitle = \"Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)\",\n    url =\"https://arxiv.org/abs/1906.02361\"\n}\n", "homepage": "https://github.com/salesforce/cos-e", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "abstractive_explanation": {"dtype": "string", "id": null, "_type": "Value"}, "extractive_explanation": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "cos_e", "config_name": "v1.0", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2077517, "num_examples": 7610, "dataset_name": "cos_e"}, "validation": {"name": "validation", "num_bytes": 261887, "num_examples": 950, "dataset_name": "cos_e"}}, "download_checksums": {"https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/train_rand_split.jsonl": {"num_bytes": 2160200, "checksum": "1989ce97e24d8572113d6a18f44e0f11ee9d206fb9bf9a1133937645583e697e"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/dev_rand_split.jsonl": {"num_bytes": 268531, "checksum": "790dd2a8492e7f3b51ded04116de603115b7acaded32ea84f6a7101f9d571ac1"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/test_rand_split_no_answers.jsonl": {"num_bytes": 250752, "checksum": "b9c3d1319667ea1569be6f7b3ed0546bd8222d2f3a759f928307343a0282e190"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/cose_dev_v1.0_processed.jsonl": {"num_bytes": 182444, "checksum": "ab7b8ac91bca1a6ba798816af6aca703a739f576c919360ddc376d9d3046be53"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.0/cose_train_v1.0_processed.jsonl": {"num_bytes": 1433393, "checksum": "df9f83ac4891f38e0771470858d5f1c4b5bb08fee5c53f38f9df9b3d3675ea74"}}, "download_size": 4295320, "dataset_size": 2339404, "size_in_bytes": 6634724}, "v1.11": {"description": "\nCommon Sense Explanations (CoS-E) allows for training language models to\nautomatically generate explanations that can be used during training and\ninference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.\n", "citation": "\n@inproceedings{rajani2019explain,\n     title = \"Explain Yourself! Leveraging Language models for Commonsense Reasoning\",\n    author = \"Rajani, Nazneen Fatema  and\n      McCann, Bryan  and\n      Xiong, Caiming  and\n      Socher, Richard\",\n      year=\"2019\",\n    booktitle = \"Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)\",\n    url =\"https://arxiv.org/abs/1906.02361\"\n}\n", "homepage": "https://github.com/salesforce/cos-e", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "abstractive_explanation": {"dtype": "string", "id": null, "_type": "Value"}, "extractive_explanation": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "cos_e", "config_name": "v1.11", "version": {"version_str": "1.11.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 11, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2717420, "num_examples": 9741, "dataset_name": "cos_e"}, "validation": {"name": "validation", "num_bytes": 331760, "num_examples": 1221, "dataset_name": "cos_e"}}, "download_checksums": {"https://s3.amazonaws.com/commensenseqa/train_rand_split.jsonl": {"num_bytes": 3785890, "checksum": "58ffa3c8472410e24b8c43f423d89c8a003d8284698a6ed7874355dedd09a2fb"}, "https://s3.amazonaws.com/commensenseqa/dev_rand_split.jsonl": {"num_bytes": 471653, "checksum": "3210497fdaae614ac085d9eb873dd7f4d49b6f965a93adadc803e1229fd8a02a"}, "https://s3.amazonaws.com/commensenseqa/test_rand_split_no_answers.jsonl": {"num_bytes": 423148, "checksum": "b426896d71a9cd064cf01cfaf6e920817c51701ef66028883ac1af2e73ad5f29"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.11/cose_dev_v1.11_processed.jsonl": {"num_bytes": 200867, "checksum": "a8367c94901ba249e48bcec76eaff9e7b91cec0f0e4d94879975d7d1b952bc41"}, "https://raw.githubusercontent.com/salesforce/cos-e/master/data/v1.11/cose_train_v1.11_processed.jsonl": {"num_bytes": 1653976, "checksum": "4c0ccfd34243cf7af62b441643437769663edcb980b991487f766b97a547e9bd"}}, "download_size": 6535534, "dataset_size": 3049180, "size_in_bytes": 9584714}}

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