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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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.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
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.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
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"default": {"description": "PyTorch original implementation of Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset\n", "citation": "@inproceedings{rashkin2019towards,\n  title = {Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset},\n  author = {Hannah Rashkin and Eric Michael Smith and Margaret Li and Y-Lan Boureau},\n  booktitle = {ACL},\n  year = {2019},\n}\n", "homepage": "https://github.com/facebookresearch/EmpatheticDialogues", "license": "", "features": {"conv_id": {"dtype": "string", "id": null, "_type": "Value"}, "utterance_idx": {"dtype": "int32", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "prompt": {"dtype": "string", "id": null, "_type": "Value"}, "speaker_idx": {"dtype": "int32", "id": null, "_type": "Value"}, "utterance": {"dtype": "string", "id": null, "_type": "Value"}, "selfeval": {"dtype": "string", "id": null, "_type": "Value"}, "tags": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "empathetic_dialogues", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 3011332, "num_examples": 10943, "dataset_name": "empathetic_dialogues"}, "train": {"name": "train", "num_bytes": 19040509, "num_examples": 76673, "dataset_name": "empathetic_dialogues"}, "validation": {"name": "validation", "num_bytes": 3077481, "num_examples": 12030, "dataset_name": "empathetic_dialogues"}}, "download_checksums": {"https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/empatheticdialogues.tar.gz": {"num_bytes": 28022709, "checksum": "56f234d77b7dd1f005fd365bb17769cfe346c3c84295b69bc069c8ccb83be03d"}}, "download_size": 28022709, "dataset_size": 25129322, "size_in_bytes": 53152031}}

dummy/0.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:236f42ae807d4795c7569fd0cb5e22614d5da4c292bbe859c6077c226fc01772
+size 1800

empathetic_dialogues.py

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+"""TODO(empathetic_dialogues): Add a description here."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import os
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{rashkin2019towards,
+  title = {Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset},
+  author = {Hannah Rashkin and Eric Michael Smith and Margaret Li and Y-Lan Boureau},
+  booktitle = {ACL},
+  year = {2019},
+}
+"""
+
+_DESCRIPTION = """\
+PyTorch original implementation of Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset
+"""
+_URL = "https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/empatheticdialogues.tar.gz"
+
+
+class EmpatheticDialogues(datasets.GeneratorBasedBuilder):
+    """TODO(empathetic_dialogues): Short description of my dataset."""
+
+    # TODO(empathetic_dialogues): Set up version.
+    VERSION = datasets.Version("0.1.0")
+
+    def _info(self):
+        # TODO(empathetic_dialogues): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "conv_id": datasets.Value("string"),
+                    "utterance_idx": datasets.Value("int32"),
+                    "context": datasets.Value("string"),
+                    "prompt": datasets.Value("string"),
+                    "speaker_idx": datasets.Value("int32"),
+                    "utterance": datasets.Value("string"),
+                    "selfeval": datasets.Value("string"),
+                    "tags": datasets.Value("string")
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://github.com/facebookresearch/EmpatheticDialogues",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(empathetic_dialogues): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        dl_dir = dl_manager.download_and_extract(_URL)
+        data_dir = os.path.join(dl_dir, "empatheticdialogues")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(data_dir, "train.csv")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(data_dir, "valid.csv")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(data_dir, "test.csv")},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        # TODO(empathetic_dialogues): Yields (key, example) tuples from the dataset
+        with open(filepath, encoding="utf-8") as f:
+            data = csv.DictReader(f)
+            for id_, row in enumerate(data):
+                utterance = row["utterance"]
+                speaker_id = int(row["speaker_idx"])
+                context = row["context"]
+                conv_id = row["conv_id"]
+                tags = row["tags"] if row["tags"] else ""
+                selfeval = row["selfeval"] if row["selfeval"] else ""
+                utterance_id = int(row["utterance_idx"])
+                prompt = row["prompt"]
+                yield id_, {
+                    "utterance": utterance,
+                    "utterance_idx": utterance_id,
+                    "context": context,
+                    "speaker_idx": speaker_id,
+                    "conv_id": conv_id,
+                    "selfeval": selfeval,
+                    "prompt": prompt,
+                    "tags": tags,
+                }