Delete codex-math-qa.py

codex-math-qa.py

@@ -1,156 +0,0 @@
-# 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.
-"""TODO: Add a description here."""
-
-import json
-import datasets
-
-
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
-_CITATION = """\
-"""
-
-# TODO: Add description of the dataset here
-# You can copy an official description
-_DESCRIPTION = """\
-Solution by codex-davinci-002 for math_qa
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = ""
-
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-
-# TODO: Add link to the official dataset URLs here
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_BASE_URL = 'https://huggingface.co/datasets/theblackcat102/codex-math-qa/resolve/main/'
-
-
-
-class CodexMathQA(datasets.GeneratorBasedBuilder):
-
-    VERSION = datasets.Version("1.0.0")
-
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="main", version=VERSION, description="training sets from math qa"),
-        datasets.BuilderConfig(name="rational", version=VERSION, description="split with rationale text in prompt")
-    ]
-
-
-    DEFAULT_CONFIG_NAME = "main"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "model_name":datasets.Value("string"),
-                "question":datasets.Value("string"),
-                "reply":datasets.Value("string"),
-                "ping_date":datasets.Value("string"),
-                "elapsed": datasets.Value("float64")
-            }
-        )
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        if "main" == self.config.name:
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    gen_kwargs={
-                        "filepath": dl_manager.download_and_extract(
-                                    _BASE_URL+'train.jsonl'
-                        ),
-                        "split": "train",
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={
-                        "filepath": dl_manager.download_and_extract(
-                                    _BASE_URL+'test.jsonl'
-                        ),
-                        "split": "test",
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    gen_kwargs={
-                         "filepath": dl_manager.download_and_extract(
-                                    _BASE_URL+'validation.jsonl'
-                        ),
-                        "split": "validation",
-                    },
-                ),
-            ]
-        elif "rational" == self.config.name:
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={
-                        "filepath": dl_manager.download_and_extract(
-                                    _BASE_URL+'rational-test.jsonl'
-                        ),
-                        "split": "test",
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    gen_kwargs={
-                         "filepath": dl_manager.download_and_extract(
-                                    _BASE_URL+'rational-val.jsonl'
-                        ),
-                        "split": "validation",
-                    },
-                ),
-            ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, split):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        with open(filepath, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                data = json.loads(row)
-                yield key, {
-                    "model_name": data["model_name"],
-                    "question": data["question"],
-                    "reply": data["reply"],
-                    "ping_date": data["ping_date"],
-                    "elapsed": data["elapsed"],
-                }