Add Kaggle preset conversion upload script (keras-team#2205)

* Add preset conversion upload script

* Fix formatting

keras_cv/tools/convert_presets.py

@@ -0,0 +1,107 @@
+# Copyright 2023 The KerasCV 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
+#
+#     https://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 shutil
+
+import keras_cv  # noqa: E402
+from keras_cv.src.utils.preset_utils import save_to_preset  # noqa: E402
+
+BUCKET = "keras-cv-kaggle"
+
+# Save and upload Backbone presets
+
+backbone_models = [
+    keras_cv.models.ResNetBackbone,
+    keras_cv.models.ResNet18Backbone,
+    keras_cv.models.ResNet34Backbone,
+    keras_cv.models.ResNet50Backbone,
+    keras_cv.models.ResNet101Backbone,
+    keras_cv.models.ResNet152Backbone,
+    keras_cv.models.ResNetV2Backbone,
+    keras_cv.models.ResNet18V2Backbone,
+    keras_cv.models.ResNet34V2Backbone,
+    keras_cv.models.ResNet50V2Backbone,
+    keras_cv.models.ResNet101V2Backbone,
+    keras_cv.models.ResNet152V2Backbone,
+    keras_cv.models.YOLOV8Backbone,
+    keras_cv.models.MobileNetV3Backbone,
+    keras_cv.models.MobileNetV3SmallBackbone,
+    keras_cv.models.MobileNetV3LargeBackbone,
+    keras_cv.models.EfficientNetV2Backbone,
+    keras_cv.models.EfficientNetV2B0Backbone,
+    keras_cv.models.EfficientNetV2B1Backbone,
+    keras_cv.models.EfficientNetV2B2Backbone,
+    keras_cv.models.EfficientNetV2B3Backbone,
+    keras_cv.models.EfficientNetV2SBackbone,
+    keras_cv.models.EfficientNetV2MBackbone,
+    keras_cv.models.EfficientNetV2LBackbone,
+]
+for backbone_cls in backbone_models:
+    for preset in backbone_cls.presets:
+        backbone = backbone_cls.from_preset(preset)
+        save_to_preset(
+            backbone,
+            preset,
+            config_filename="config.json",
+        )
+        # Delete first to clean up any exising version.
+        os.system(f"gsutil rm -rf gs://{BUCKET}/{preset}")
+        os.system(f"gsutil cp -r {preset} gs://{BUCKET}/{preset}")
+        for root, _, files in os.walk(preset):
+            for file in files:
+                path = os.path.join(BUCKET, root, file)
+                os.system(
+                    f"gcloud storage objects update gs://{path} "
+                    "--add-acl-grant=entity=AllUsers,role=READER"
+                )
+
+
+# Save and upload task presets
+
+task_models = [
+    keras_cv.models.RetinaNet,
+    keras_cv.models.YOLOV8Detector,
+    keras_cv.models.ImageClassifier,
+    keras_cv.models.DeepLabV3Plus,
+]
+for task_cls in task_models:
+    # Remove backbone-specific keys
+    task_preset_keys = set(task_cls.presets) ^ set(task_cls.backbone_presets)
+    for preset in task_preset_keys:
+        preset_metadata = task_cls.presets[preset]
+        kwargs = {}
+        if task_cls in [
+            keras_cv.models.RetinaNet,
+            keras_cv.models.YOLOV8Detector,
+        ]:
+            kwargs.update({"bounding_box_format": "xywh"})
+            task = task_cls.from_preset(preset, **kwargs)
+        else:
+            task = task_cls.from_preset(preset)
+        save_to_preset(
+            task,
+            preset,
+            config_filename="config.json",
+        )
+        # Delete first to clean up any exising version.
+        os.system(f"gsutil rm -rf gs://{BUCKET}/{preset}")
+        os.system(f"gsutil cp -r {preset} gs://{BUCKET}/{preset}")
+        for root, _, files in os.walk(preset):
+            for file in files:
+                path = os.path.join(BUCKET, root, file)
+                os.system(
+                    f"gcloud storage objects update gs://{path} "
+                    "--add-acl-grant=entity=AllUsers,role=READER"
+                )

keras_cv/utils/preset_utils_test.py

@@ -1,4 +1,4 @@
-# Copyright 2023 The KerasNLP Authors
+# Copyright 2023 The KerasCV Authors
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.