Delete loading script

sms_spam.py

@@ -1,92 +0,0 @@
-# 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
-"""SMS Spam Collection Data Set"""
-
-
-import os
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_CITATION = """\
-@inproceedings{Almeida2011SpamFiltering,
-  title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
-  author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
-  year={2011},
-  booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
-}
-"""
-
-_DESCRIPTION = """\
-The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
-It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.
-"""
-
-_DATA_URL = "http://archive.ics.uci.edu/ml/machine-learning-databases/00228/smsspamcollection.zip"
-
-
-class SmsSpam(datasets.GeneratorBasedBuilder):
-    """SMS Spam Collection Data Set"""
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="plain_text",
-            version=datasets.Version("1.0.0", ""),
-            description="Plain text import of SMS Spam Collection Data Set",
-        )
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "sms": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(names=["ham", "spam"]),
-                }
-            ),
-            supervised_keys=("sms", "label"),
-            homepage="http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="sms", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        dl_dir = dl_manager.download_and_extract(_DATA_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, "SMSSpamCollection")}
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-
-        with open(filepath, encoding="utf-8") as sms_file:
-            for idx, line in enumerate(sms_file):
-                fields = line.split("\t")
-
-                if fields[0] == "ham":
-                    label = 0
-                else:
-                    label = 1
-
-                yield idx, {
-                    "sms": fields[1],
-                    "label": label,
-                }