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tools/checkpoint_conversion Expand file tree Collapse file tree 15 files changed +2408
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lines changed Original file line number Diff line number Diff line change 38
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pip install torch>=2.0.1+cpu
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pip install "jax[cpu]"
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pip install keras-core
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+ pip install keras-nlp-nightly --no-deps
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+ pip install tensorflow-text==2.15
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pip install -e ".[tests]" --progress-bar off --upgrade
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- name : Test with pytest
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env :
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run : |
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pip install -r requirements.txt
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pip install -e ".[tests]" --progress-bar off --upgrade
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+ pip install keras-nlp-nightly
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- name : Test with pytest
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env :
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TEST_CUSTOM_OPS : false # TODO(ianstenbit): test custom ops, or figure out what our story is here
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pip install --extra-index-url https://download.pytorch.org/whl/cpu torch==2.1.0+cpu
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pip install torchvision~=0.16.0
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pip install " jax[cpu]"
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+ pip install keras-nlp-nightly --no-deps
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+ pip install tensorflow-text==2.15
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elif [ " $KERAS_BACKEND " == " tensorflow" ]
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then
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echo " TensorFlow backend detected."
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pip install -r requirements-tensorflow-cuda.txt --progress-bar off
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+ pip install keras-nlp-nightly
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elif [ " $KERAS_BACKEND " == " jax" ]
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then
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echo " JAX backend detected."
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pip install -r requirements-jax-cuda.txt --progress-bar off
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+ pip install keras-nlp-nightly
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elif [ " $KERAS_BACKEND " == " torch" ]
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then
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echo " PyTorch backend detected."
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pip install -r requirements-torch-cuda.txt --progress-bar off
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+ pip install keras-nlp-nightly
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fi
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pip install --no-deps -e " ." --progress-bar off
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from keras_cv .models .backbones .vit_det .vit_det_aliases import ViTDetLBackbone
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from keras_cv .models .backbones .vit_det .vit_det_backbone import ViTDetBackbone
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from keras_cv .models .classification .image_classifier import ImageClassifier
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+ from keras_cv .models .feature_extractor .clip import CLIP
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from keras_cv .models .object_detection .retinanet .retinanet import RetinaNet
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from keras_cv .models .object_detection .yolo_v8 .yolo_v8_backbone import (
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YOLOV8Backbone ,
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+ # Copyright 2023 The KerasCV Authors
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # https://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+ # Copyright 2023 The KerasCV Authors
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # https://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+
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+ from keras_cv .models .feature_extractor .clip .clip_image_model import (
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+ CLIPImageEncoder ,
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+ )
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+ from keras_cv .models .feature_extractor .clip .clip_model import CLIP
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+ from keras_cv .models .feature_extractor .clip .clip_processor import CLIPProcessor
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+ from keras_cv .models .feature_extractor .clip .clip_text_model import (
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+ CLIPTextEncoder ,
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+ )
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+ from keras_cv .models .feature_extractor .clip .clip_tokenizer import CLIPTokenizer
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