import: copybara import of the project

Project import generated by Copybara.

GitOrigin-RevId: bc26ddfdecf9cfa16a123c254adfe31b2111b4ee

.gitattributes

@@ -25,3 +25,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text
+*.jsonl filter=lfs diff=lfs merge=lfs -text

coda.py

@@ -0,0 +1,90 @@
+# Copyright 2021 Cory Paik. All Rights Reserved.
+#
+# 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.
+# ==============================================================================
+""" The Color Dataset (CoDa)
+
+ TODO
+"""
+import json
+
+import datasets
+
+_CITATION = """\
+"""
+
+_DESCRIPTION = """\
+"""
+
+_HOMEPAGE = 'https://github.com/nala-cub/coda'
+_LICENSE = 'Apache 2.0'
+
+_URL = 'https://huggingface.co/datasets/corypaik/coda/resolve/main/data'
+
+_URLs = {
+    'default': {
+        'train': f'{_URL}/default_train.jsonl',
+        'validation': f'{_URL}/default_validation.jsonl',
+        'test': f'{_URL}/default_test.jsonl',
+    }
+}
+
+
+class Coda(datasets.GeneratorBasedBuilder):
+
+  VERSION = datasets.Version('1.0.0')
+
+  # TODO(corypaik): add object and annotation configs.
+
+  def _info(self):
+    features = datasets.Features({
+        'class_id':
+            datasets.Value('string'),
+        'display_name':
+            datasets.Value('string'),
+        'ngram':
+            datasets.Value('string'),
+        'label':
+            datasets.Sequence(datasets.Value('float')),
+        'object_group':
+            datasets.ClassLabel(names=('Single', 'Multi', 'Any')),
+        'text':
+            datasets.Value('string'),
+        'template_group':
+            datasets.ClassLabel(names=('clip-imagenet', 'text-masked')),
+        'template_idx':
+            datasets.Value('int32')
+    })
+    return datasets.DatasetInfo(description=_DESCRIPTION,
+                                features=features,
+                                supervised_keys=None,
+                                homepage=_HOMEPAGE,
+                                license=_LICENSE,
+                                citation=_CITATION)
+
+  def _split_generators(self, dl_manager):
+    """ Returns SplitGenerators."""
+    files = dl_manager.download_and_extract(_URLs[self.config.name])
+    return [
+        datasets.SplitGenerator(datasets.Split.TRAIN,
+                                gen_kwargs={'path': files['train']}),
+        datasets.SplitGenerator(datasets.Split.VALIDATION,
+                                gen_kwargs={'path': files['validation']}),
+        datasets.SplitGenerator(datasets.Split.TEST,
+                                gen_kwargs={'path': files['test']}),
+    ]
+
+  def _generate_examples(self, path):
+    with open(path, 'r') as f:
+      for _id, line in enumerate(f.readlines()):
+        yield _id, json.loads(line)