add loading script

RenderedSST2.py

@@ -0,0 +1,121 @@
+# 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: Address all TODOs and remove all explanatory comments
+"""TODO: Add a description here."""
+
+
+import csv
+import json
+import os
+from pathlib import Path
+
+import datasets
+
+_CITATION = """\
+@article{DBLP:journals/corr/abs-2103-00020,
+  author    = {Alec Radford and
+               Jong Wook Kim and
+               Chris Hallacy and
+               Aditya Ramesh and
+               Gabriel Goh and
+               Sandhini Agarwal and
+               Girish Sastry and
+               Amanda Askell and
+               Pamela Mishkin and
+               Jack Clark and
+               Gretchen Krueger and
+               Ilya Sutskever},
+  title     = {Learning Transferable Visual Models From Natural Language Supervision},
+  journal   = {CoRR},
+  volume    = {abs/2103.00020},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2103.00020},
+  eprinttype = {arXiv},
+  eprint    = {2103.00020},
+  timestamp = {Thu, 04 Mar 2021 17:00:40 +0100},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2103-00020.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
+"""
+
+_HOMEPAGE = "https://github.com/openai/CLIP/blob/main/data/rendered-sst2.md"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+_URL = "https://openaipublic.azureedge.net/clip/data/rendered-sst2.tgz"
+
+_NAMES = ["negative", "positive"]
+
+
+class SST2Dataset(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "image": datasets.Image(),
+                "label": datasets.ClassLabel(names=_NAMES),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_URL)
+        data_dir = Path(data_dir) / "rendered-sst2"
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "dir": data_dir / "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "dir": data_dir / "valid",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "dir": data_dir / "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, dir):
+        index = -1
+        for image_path in (dir / "negative").iterdir():
+            index += 1
+            record = {"label": "negative", "image": str(image_path)}
+            yield index, record
+        for image_path in (dir / "positive").iterdir():
+            index += 1
+            record = {"label": "negative", "image": str(image_path)}
+            yield index, record