Add CLIP to KerasCV

.github/workflows/actions.yml

@@ -38,6 +38,8 @@ jobs:
         pip install torch>=2.0.1+cpu
         pip install "jax[cpu]"
         pip install keras-core
+        pip install keras-nlp-nightly --no-deps
+        pip install tensorflow-text==2.15
         pip install -e ".[tests]" --progress-bar off --upgrade
     - name: Test with pytest
       env:
@@ -75,6 +77,7 @@ jobs:
       run: |
         pip install -r requirements.txt
         pip install -e ".[tests]" --progress-bar off --upgrade
+        pip install keras-nlp-nightly
     - name: Test with pytest
       env:
         TEST_CUSTOM_OPS: false # TODO(ianstenbit): test custom ops, or figure out what our story is here

.kokoro/github/ubuntu/gpu/build.sh

@@ -29,21 +29,26 @@ then
    pip install --extra-index-url https://download.pytorch.org/whl/cpu torch==2.1.0+cpu
    pip install torchvision~=0.16.0
    pip install "jax[cpu]"
+   pip install keras-nlp-nightly --no-deps
+   pip install tensorflow-text==2.15
 
 elif [ "$KERAS_BACKEND" == "tensorflow" ]
 then
    echo "TensorFlow backend detected."
    pip install -r requirements-tensorflow-cuda.txt --progress-bar off
+   pip install keras-nlp-nightly
 
 elif [ "$KERAS_BACKEND" == "jax" ]
 then
    echo "JAX backend detected."
    pip install -r requirements-jax-cuda.txt --progress-bar off
+   pip install keras-nlp-nightly
 
 elif [ "$KERAS_BACKEND" == "torch" ]
 then
    echo "PyTorch backend detected."
    pip install -r requirements-torch-cuda.txt --progress-bar off
+   pip install keras-nlp-nightly
 fi
 
 pip install --no-deps -e "." --progress-bar off

keras_cv/models/__init__.py

@@ -183,6 +183,7 @@
 from keras_cv.models.backbones.vit_det.vit_det_aliases import ViTDetLBackbone
 from keras_cv.models.backbones.vit_det.vit_det_backbone import ViTDetBackbone
 from keras_cv.models.classification.image_classifier import ImageClassifier
+from keras_cv.models.feature_extractor.clip import CLIP
 from keras_cv.models.object_detection.retinanet.retinanet import RetinaNet
 from keras_cv.models.object_detection.yolo_v8.yolo_v8_backbone import (
     YOLOV8Backbone,

keras_cv/models/feature_extractor/__init__.py

@@ -0,0 +1,13 @@
+# 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.

keras_cv/models/feature_extractor/clip/__init__.py

@@ -0,0 +1,23 @@
+# 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.
+
+from keras_cv.models.feature_extractor.clip.clip_image_model import (
+    CLIPImageEncoder,
+)
+from keras_cv.models.feature_extractor.clip.clip_model import CLIP
+from keras_cv.models.feature_extractor.clip.clip_processor import CLIPProcessor
+from keras_cv.models.feature_extractor.clip.clip_text_model import (
+    CLIPTextEncoder,
+)
+from keras_cv.models.feature_extractor.clip.clip_tokenizer import CLIPTokenizer