Add data script

codequeries.py

@@ -0,0 +1,223 @@
+# coding=utf-8
+# Copyright 2022 CodeQueries 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.
+
+"""The CodeQueries benchmark."""
+
+
+import json
+import os
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CODEQUERIES_CITATION = """\
+@article{codequeries2022,
+  title={Learning to Answer Semantic Queries over Code},
+  author={A, B, C, D, E, F},
+  journal={arXiv preprint arXiv:<.>},
+  year={2022}
+}
+"""
+
+_IDEAL_DESCRIPTION = """\
+CodeQueries Ideal setup.
+
+"""
+
+_PREFIX_DESCRIPTION = """\
+CodeQueries Prefix setup."""
+
+_SLIDING_WINDOW_DESCRIPTION = """\
+CodeQueries Sliding window setup."""
+
+_FILE_IDEAL_DESCRIPTION = """\
+CodeQueries File level Ideal setup."""
+
+_TWOSTEP_DESCRIPTION = """\
+CodeQueries Twostep setup."""
+
+
+class CodequeriesConfig(datasets.BuilderConfig):
+    """BuilderConfig for Codequeries."""
+
+    def __init__(self, features, citation, **kwargs):
+        """BuilderConfig for Codequeries.
+
+        Args:
+          features: `list[string]`, list of the features that will appear in the
+            feature dict. Should not include "label".
+          citation: `string`, citation for the data set.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        # Version history:
+        # 1.0.0: Initial version.
+        super(CodequeriesConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.features = features
+        self.citation = citation
+
+
+class Codequeries(datasets.GeneratorBasedBuilder):
+    """The Codequeries benchmark."""
+
+    BUILDER_CONFIGS = [
+        CodequeriesConfig(
+            name="ideal",
+            description=_IDEAL_DESCRIPTION,
+            features=["query_name", "context_blocks", "answer_spans",
+                      "supporting_fact_spans", "code_file_path", "example_type",
+                      "subtokenized_input_sequence", "label_sequence"],
+            citation=_CODEQUERIES_CITATION,
+            # homepage="",
+            # data_url="",
+            # url="https://github.com/google-research-datasets/boolean-questions",
+        ),
+        # CodequeriesConfig(
+        #     name="prefix",
+        #     description=_PREFIX_DESCRIPTION,
+        #     features=["query_name", "context_blocks", "answer_spans",
+        #               "supporting_fact_spans", "code_file_path", "example_type",
+        #               "subtokenized_input_sequence", "label_sequence"],
+        #     citation=_CODEQUERIES_CITATION,
+        # ),
+        # CodequeriesConfig(
+        #     name="sliding_window",
+        #     description=_SLIDING_WINDOW_DESCRIPTION,
+        #     features=["query_name", "context_blocks", "answer_spans",
+        #               "supporting_fact_spans", "code_file_path", "example_type",
+        #               "subtokenized_input_sequence", "label_sequence"],
+        #     citation=_CODEQUERIES_CITATION,
+        # ),
+        CodequeriesConfig(
+            name="file_ideal",
+            description=_FILE_IDEAL_DESCRIPTION,
+            features=["query_name", "context_blocks", "answer_spans",
+                      "supporting_fact_spans", "code_file_path", "example_type",
+                      "subtokenized_input_sequence", "label_sequence"],
+            citation=_CODEQUERIES_CITATION,
+        ),
+        # CodequeriesConfig(
+        #     name="twostep",
+        #     description=_TWOSTEP_DESCRIPTION,
+        #     features=["query_name", "context_blocks", "answer_spans",
+        #               "supporting_fact_spans", "code_file_path", "example_type",
+        #               "subtokenized_input_sequence", "label_sequence"],
+        #     citation=_CODEQUERIES_CITATION,
+        # ),
+    ]
+
+    # DEFAULT_CONFIG_NAME = "ideal"
+
+    def _info(self):
+        # features = {feature: datasets.Value("string") for feature in self.config.features}
+        features = {}
+        features["query_name"] = datasets.Value("string")
+        features["context_blocks"] = datasets.features.Sequence(
+            {
+                "content": datasets.Value("string"),
+                "metadata": datasets.Value("string"),
+                "header": datasets.Value("string")
+            }
+        )
+        features["answer_spans"] = datasets.features.Sequence(
+            {
+                'span': datasets.Value("string"),
+                'start_line': datasets.Value("int32"),
+                'start_column': datasets.Value("int32"),
+                'end_line': datasets.Value("int32"),
+                'end_column': datasets.Value("int32")
+            }
+        )
+        features["supporting_fact_spans"] = datasets.features.Sequence(
+            {
+                'span': datasets.Value("string"),
+                'start_line': datasets.Value("int32"),
+                'start_column': datasets.Value("int32"),
+                'end_line': datasets.Value("int32"),
+                'end_column': datasets.Value("int32")
+            }
+        )
+        features["code_file_path"] = datasets.Value("string")
+        features["example_type"] = datasets.Value("int32")
+        features["subtokenized_input_sequence"] = datasets.features.Sequence(datasets.Value("string"))
+        features["label_sequence"] = datasets.features.Sequence(datasets.Value("int32"))
+
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=datasets.Features(features),
+            homepage=self.config.url,
+            citation=_CODEQUERIES_CITATION,
+        )
+
+    def _split_generators(self):
+        dl_dir = ""
+        if self.config.name in ["prefix", "sliding_window", "file_ideal", "twostep"]:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir, self.config.name + "_test.json"),
+                        "split": datasets.Split.TEST,
+                    },
+                ),
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir, self.config.name + "_train.json"),
+                        "split": datasets.Split.TRAIN,
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir, self.config.name + "_val.json"),
+                        "split": datasets.Split.VALIDATION,
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepath": os.path.join(dl_dir, self.config.name + "_test.json"),
+                        "split": datasets.Split.TEST,
+                    },
+                ),
+            ]
+
+    def _generate_examples(self, filepath, split):
+        if self.config.name in ["prefix", "sliding_window", "file_ideal", "twostep"]:
+            assert split == datasets.Split.TEST
+        logger.info("generating examples from = %s", filepath)
+
+        with open(filepath, encoding="utf-8") as f:
+            key = 0
+            for line in f:
+                row = json.loads(line)
+
+                instance_key = key + "_" + row["query_name"] + "_" + row["code_file_path"]
+                yield instance_key, {
+                    "query_name": row["query_name"],
+                    "context_blocks": row["context_blocks"],
+                    "answer_spans": row["answer_spans"],
+                    "supporting_fact_spans": row["supporting_fact_spans"],
+                    "code_file_path": row["code_file_path"],
+                    "example_type": row["example_type"],
+                    "subtokenized_input_sequence ": row["subtokenized_input_sequence "],
+                    "label_sequence": row["label_sequence"],
+                }
+                key += 1