Adding DNLI

.gitattributes

@@ -57,3 +57,8 @@ dnli/dialogue_nli/dialogue_nli_train.jsonl filter=lfs diff=lfs merge=lfs -text
 dnli/dialogue_nli_extra/dialogue_nli_EXTRA_uu_dev.jsonl filter=lfs diff=lfs merge=lfs -text
 dnli/dialogue_nli_extra/dialogue_nli_EXTRA_uu_test.jsonl filter=lfs diff=lfs merge=lfs -text
 dnli/dialogue_nli_extra/dialogue_nli_EXTRA_uu_train.jsonl filter=lfs diff=lfs merge=lfs -text
+dnli.zip filter=lfs diff=lfs merge=lfs -text
+dialogue_nli/dialogue_nli/dialogue_nli_train.jsonl filter=lfs diff=lfs merge=lfs -text
+dialogue_nli/dialogue_nli_extra/dialogue_nli_EXTRA_uu_dev.jsonl filter=lfs diff=lfs merge=lfs -text
+dialogue_nli/dialogue_nli_extra/dialogue_nli_EXTRA_uu_test.jsonl filter=lfs diff=lfs merge=lfs -text
+dialogue_nli/dialogue_nli_extra/dialogue_nli_EXTRA_uu_train.jsonl filter=lfs diff=lfs merge=lfs -text

dialogue_nli.py

@@ -0,0 +1,118 @@
+import csv
+import json
+import logging as logger
+import os
+
+import datasets
+
+
+_CITATION = """\
+@misc{welleck2019dialogue,
+      title={Dialogue Natural Language Inference}, 
+      author={Sean Welleck and Jason Weston and Arthur Szlam and Kyunghyun Cho},
+      year={2019},
+      eprint={1811.00671},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+Dialogue NLI is a dataset that addresses the issue of consistency in dialogue models.
+"""
+
+_URL = "dnli.zip"
+
+_HOMEPAGE = "https://wellecks.github.io/dialogue_nli/"
+
+_LICENSE = "MIT"
+
+class Dialogue_NLI(datasets.GeneratorBasedBuilder):
+    """DNLI"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="dialogue_nli", version=VERSION, description="dnli"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "dialogue_nli"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                    "premise": datasets.Value("string"),
+                    "hypothesis": datasets.Value("string"),
+                    # "triple1": datasets.Value("string"),
+                    # "triple2": datasets.Value("string"),                
+                    "dtype": datasets.Value("string"),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        data_dir = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "dnli/dialogue_nli/dialogue_nli_train.jsonl"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "dnli/dialogue_nli/dialogue_nli_dev.jsonl"),
+                    "split": "dev",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "dnli/dialogue_nli/dialogue_nli_test.jsonl"),
+                    "split": "test"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        with open(filepath) as f:
+            data = json.load(f)
+            # print(data)
+            for example in data:
+                label = example.get("label", "").strip()
+                id_ = example.get("id", "").strip()
+                hypothesis = example.get("sentence1", "").strip()
+                premise = example.get("sentence2", "").strip()
+                dtype = example.get("dtype", "").strip()
+
+                # Features currently used are "context", "question", and "answers".
+                # Others are extracted here for the ease of future expansions.
+                yield id_, {
+                    "premise": premise,
+                    "hypothesis": hypothesis,
+                    "id": id_,
+                    "label": label,
+                    "dtype": dtype,
+                }
+    

dnli.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1164b0d9a0a1a6006891a6d4435a6a813464bc9b1e2f1ec5ce28c47267ad5e42
+size 389584058