update

finqa.py

@@ -0,0 +1,82 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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 WikiTableQuestions dataset is a large-scale dataset for the task of question answering on semi-structured tables."""
+
+import os
+
+import datasets
+
+import json
+
+
+class FinQA(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                # "filename": datasets.Value("string"),
+                "id": datasets.Value("string"),
+                "post_text": datasets.features.Sequence(datasets.Value("string")),
+                "pre_text": datasets.features.Sequence(datasets.Value("string")),
+                "question": datasets.Value("string"),
+                "answers": datasets.Value("string"),
+                "table": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("string"))),
+            }
+        )
+        return datasets.DatasetInfo(
+            features=features,
+        )
+
+    def _split_generators(self, dl_manager):
+        train_file = "train.json"
+        dev_file = "dev.json"
+        test_file = "test.json"
+        
+        root_dir = 'finqa'
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"main_filepath": os.path.join(root_dir, train_file), "root_dir": root_dir},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"main_filepath": os.path.join(root_dir, dev_file), "root_dir": root_dir},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"main_filepath": os.path.join(root_dir, test_file), "root_dir": root_dir},
+            ),
+        ]
+
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, main_filepath, root_dir):
+        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+        with open(main_filepath, encoding="utf-8") as f:
+            # skip the first line since it is the tsv header
+            lines = json.load(f)
+            for idx, example in enumerate(lines):
+                yield idx, { \
+                "id": example['id'], \
+                "post_text": example['post_text'], \
+                "pre_text": example['pre_text'], \
+                "question": example['qa']['question'], \
+                "answers": example['qa']['answer'], \
+                "table": example['table'] 
+                }