Delete hg38.py

hg38.py

@@ -1,86 +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.
-import json
-import os
-
-import datasets
-import pandas as pd
-
-_CITATION = """\
-CITATION 
-"""
-
-_DESCRIPTION = """\
-DESCRIPTION
-"""
-
-_HOMEPAGE = "HOMEPAGE"
-
-_LICENSE = ""
-
-
-FILES = ["hg38_8k_train.jsonl", "hg38_8k_test.jsonl"]
-
-
-task_list = [
-    "hg38_8k",
-]
-
-
-class hg38Config(datasets.BuilderConfig):
-    def __init__(self, **kwargs):
-        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
-
-
-class hg38(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        hg38Config(
-            name=task_name,
-        )
-        for task_name in task_list
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "chrom":datasets.Value("string"),
-                    "start": datasets.Value("int32"),
-                    "end": datasets.Value("int32"),
-                    "seq": datasets.Value("string"),
-                }
-            ),
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download(FILES)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files[0]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files[1]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath) as jsonl_file:
-            for row, line in enumerate(jsonl_file):
-                data = json.loads(line)
-                yield row, {
-                    "chrom": data["chrom"],
-                    "start": data["start"],
-                    "end": data["end"],
-                    "seq": data["seq"],
-                }