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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blimp.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
+"""BLiMP dataset with minimal pairs of grammatical phenomena in English."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """
+@article{warstadt2019blimp,
+  title={BLiMP: A Benchmark of Linguistic Minimal Pairs for English},
+  author={Warstadt, Alex and Parrish, Alicia and Liu, Haokun and Mohananey, Anhad and Peng, Wei, and Wang, Sheng-Fu and Bowman, Samuel R},
+  journal={arXiv preprint arXiv:1912.00582},
+  year={2019}
+}
+"""
+
+_DESCRIPTION = """
+BLiMP is a challenge set for evaluating what language models (LMs) know about
+major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
+containing 1000 minimal pairs isolating specific contrasts in syntax,
+morphology, or semantics. The data is automatically generated according to
+expert-crafted grammars.
+"""
+
+_PROJECT_URL = "https://github.com/alexwarstadt/blimp/tree/master/"
+_DOWNLOAD_URL = "https://raw.githubusercontent.com/alexwarstadt/blimp/master/"
+
+
+class BlimpConfig(datasets.BuilderConfig):
+    """BuilderConfig for Blimp."""
+
+    def __init__(self, paradigm_uid, **kwargs):
+        """BuilderConfig for Blimp.
+
+        Args:
+          paradigm_uid: string, UID of the linguistic paradigm
+          **kwargs: keyword arguments forwarded to super.
+        """
+        name = paradigm_uid
+
+        description = _DESCRIPTION
+        description += ("This configuration includes the paradigm {}.").format(name)
+
+        super(BlimpConfig, self).__init__(
+            name=name, description=description, version=datasets.Version("0.1.0"), **kwargs
+        )
+
+
+class Blimp(datasets.GeneratorBasedBuilder):
+    """Minimal grammatical and ungrammatical pairs of 67 linguistic paradigms."""
+
+    all_paradigms = [
+        "adjunct_island",
+        "anaphor_gender_agreement",
+        "anaphor_number_agreement",
+        "animate_subject_passive",
+        "animate_subject_trans",
+        "causative",
+        "complex_NP_island",
+        "coordinate_structure_constraint_complex_left_branch",
+        "coordinate_structure_constraint_object_extraction",
+        "determiner_noun_agreement_1",
+        "determiner_noun_agreement_2",
+        "determiner_noun_agreement_irregular_1",
+        "determiner_noun_agreement_irregular_2",
+        "determiner_noun_agreement_with_adj_2",
+        "determiner_noun_agreement_with_adj_irregular_1",
+        "determiner_noun_agreement_with_adj_irregular_2",
+        "determiner_noun_agreement_with_adjective_1",
+        "distractor_agreement_relational_noun",
+        "distractor_agreement_relative_clause",
+        "drop_argument",
+        "ellipsis_n_bar_1",
+        "ellipsis_n_bar_2",
+        "existential_there_object_raising",
+        "existential_there_quantifiers_1",
+        "existential_there_quantifiers_2",
+        "existential_there_subject_raising",
+        "expletive_it_object_raising",
+        "inchoative",
+        "intransitive",
+        "irregular_past_participle_adjectives",
+        "irregular_past_participle_verbs",
+        "irregular_plural_subject_verb_agreement_1",
+        "irregular_plural_subject_verb_agreement_2",
+        "left_branch_island_echo_question",
+        "left_branch_island_simple_question",
+        "matrix_question_npi_licensor_present",
+        "npi_present_1",
+        "npi_present_2",
+        "only_npi_licensor_present",
+        "only_npi_scope",
+        "passive_1",
+        "passive_2",
+        "principle_A_c_command",
+        "principle_A_case_1",
+        "principle_A_case_2",
+        "principle_A_domain_1",
+        "principle_A_domain_2",
+        "principle_A_domain_3",
+        "principle_A_reconstruction",
+        "regular_plural_subject_verb_agreement_1",
+        "regular_plural_subject_verb_agreement_2",
+        "sentential_negation_npi_licensor_present",
+        "sentential_negation_npi_scope",
+        "sentential_subject_island",
+        "superlative_quantifiers_1",
+        "superlative_quantifiers_2",
+        "tough_vs_raising_1",
+        "tough_vs_raising_2",
+        "transitive",
+        "wh_island",
+        "wh_questions_object_gap",
+        "wh_questions_subject_gap",
+        "wh_questions_subject_gap_long_distance",
+        "wh_vs_that_no_gap",
+        "wh_vs_that_no_gap_long_distance",
+        "wh_vs_that_with_gap",
+        "wh_vs_that_with_gap_long_distance",
+    ]
+
+    BUILDER_CONFIGS = [BlimpConfig(paradigm_uid=paradigm) for paradigm in all_paradigms]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence_good": datasets.Value("string"),
+                    "sentence_bad": datasets.Value("string"),
+                    "field": datasets.Value("string"),
+                    "linguistics_term": datasets.Value("string"),
+                    "UID": datasets.Value("string"),
+                    "simple_LM_method": datasets.Value("bool"),
+                    "one_prefix_method": datasets.Value("bool"),
+                    "two_prefix_method": datasets.Value("bool"),
+                    "lexically_identical": datasets.Value("bool"),
+                    "pair_id": datasets.Value("int32"),
+                }
+            ),
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_PROJECT_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        cfg = self.config
+        download_urls = {cfg.name: os.path.join(_DOWNLOAD_URL, "data", cfg.name + ".jsonl")}
+
+        downloaded_files = dl_manager.download_and_extract(download_urls)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files[cfg.name]})
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, "rb") as f:
+            for line in f:
+                line_dict = json.loads(line)
+                id_ = line_dict["UID"] + "_" + line_dict["pairID"]
+                feats = {
+                    "sentence_good": line_dict["sentence_good"],
+                    "sentence_bad": line_dict["sentence_bad"],
+                    "field": line_dict["field"],
+                    "linguistics_term": line_dict["linguistics_term"],
+                    "UID": line_dict["UID"],
+                    "simple_LM_method": line_dict["simple_LM_method"],
+                    "one_prefix_method": line_dict["one_prefix_method"],
+                    "two_prefix_method": line_dict["two_prefix_method"],
+                    "lexically_identical": line_dict["lexically_identical"],
+                    "pair_id": int(line_dict["pairID"]),
+                }
+                yield id_, feats

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