Create flickr_1k_test_image_text_retrieval.py

flickr_1k_test_image_text_retrieval.py

@@ -0,0 +1,61 @@
+# coding=utf-8
+# Copyright 2022 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.
+
+import os
+
+import datasets
+import json
+
+class Dataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="TEST", version=VERSION, description="test"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "split": datasets.Value("string"),
+                }
+            ),
+            task_templates=[],
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        hf_auth_token = dl_manager.download_config.use_auth_token
+        if hf_auth_token is None:
+            raise ConnectionError(
+                "Please set use_auth_token=True or use_auth_token='<TOKEN>' to download this dataset"
+            )
+
+        downloaded_files = dl_manager.download_and_extract({
+            "examples": "test_1k_flickr.csv",
+        })
+
+        # return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=downloaded_files)]
+        return [datasets.SplitGenerator(name=datasets.Split.TEST)]
+
+
+    def _generate_examples(self, examples):
+        """Yields examples."""
+        df = pd.read_csv(examples)
+        print("HERE!?")
+        raise Exception("E")
+        for r_idx, r in df.iterrows():
+            r_dict = r.to_dict()
+            yield r_idx, r_dict