Initial change for Keras Hub #1838
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* Agg Vgg16 backbone * update names * update tests * update test * add image classifier * incorporate review comments * Update test case * update backbone test * add image classifier * classifier cleanup * code reformat * add vgg16 image classifier * make vgg generic * update doc string * update docstring * add classifier test * update tests * update docstring * address review comments * code reformat * update the configs * address review comments * fix task saved model test * update init * code reformatted
* Add ResNetV1 and ResNetV2 * Address comments
* Add CSP DarkNet * Add CSP DarkNet * snake_case function names * change use_depthwise to block_type
…Backbone` (#1769) * Add FeaturePyramidBackbone and update ResNetBackbone * Simplify the implementation * Fix CI * Make ResNetBackbone compatible with timm and add FeaturePyramidBackbone * Add conversion implementation * Update docstrings * Address comments
* Add DenseNet * fix testcase * address comments * nit * fix lint errors * move description
* add vit det vit_det_backbone * update docstring * code reformat * fix tests * address review comments * bump year on all files * address review comments * rename backbone * fix tests * change back to ViT * address review comments * update image shape
* Add MixTransformer * fix testcase * test changes and comments * lint fix * update config list * modify testcase for 2 layers
* update input_image_shape -> image_shape * update docstring example * code reformat * update tests
add missing __init__ file to vit_det
This is a temporary way to test out the keras-hub branch. - Does a global rename of all symbols during package build. - Registers the "old" name on symbol export for saving compat. - Adds a github action to publish every commit to keras-hub as a new package. - Removes our descriptions on PyPI temporarily, until we want to message this more broadly.
* Add `CLIPTokenizer`, `T5XXLTokenizer`, `CLIPTextEncoder` and `T5XXLTextEncoder`. * Make CLIPTextEncoder as Backbone * Add `T5XXLPreprocessor` and remove `T5XXLTokenizer` Add `CLIPPreprocessor` * Use `tf = None` at the top * Replace manual implementation of `CLIPAttention` with `MultiHeadAttention`
* Bounding box utils * - Correct test cases * - Remove hard tensorflow dtype * - fix api gen * - Fix import for test cases - Use setup for converters test case * - fix api_gen issue * - FIx api gen * - Fix api gen error * - Correct test cases as per new api changes
* mobilenet_v3 added in keras-nlp * minor bug fixed in mobilenet_v3_backbone * formatting corrected * refactoring backbone * correct_pad_downsample method added * refactoring backbone * parameters updated * Testcaseupdated, expected output shape corrected * code formatted with black * testcase updated * refactoring and description added * comments updated * added mobilenet v1 and v2 * merge conflict resolved * version arg removed, and config options added * input_shape changed to image_shape in arg * config updated * input shape corrected * comments resolved * activation function format changed * minor bug fixed * minor bug fixed * added vision_backbone_test * channel_first bug resolved * channel_first cases working * comments resolved * formatting fixed * refactoring --------- Co-authored-by: ushareng <usha.rengaraju@gmail.com>
* migrating efficientnet models to keras-hub * merging changes from other sources * autoformatting pass * initial consolidation of efficientnet_backbone * most updates and removing separate implementation * cleanup, autoformatting, keras generalization * removed layer examples outside of effiicient net * many, mainly documentation changes, small test fixes
* Add ResNet_vd to ResNet backbone * Addressed requested parameter changes * Fixed tests and updated comments * Added new parameters to docstring
* Add `VAEImageDecoder` for StableDiffusionV3 * Use `keras.Model` for `VAEImageDecoder` and follows the coding style in `VAEAttention`
* add pyramid outputs * fix testcase * format fix * make common testcase for pyramid outputs * change default shape * simplify testcase * test case change and add channel axis
* - Add formats, iou, utils for bounding box * - Add `AnchorGenerator`, `BoxMatcher` and `NonMaxSupression` layers * - Remove scope_name not required. * use default keras name scope * - Correct format error * - Remove layers as of now and keep them at model level till keras core supports them * - Correct api_gen
- Add presets. - Add converter script. - Add preprocessing with auto resizing.
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This isn't to review, it's everyone's changes over the last couple weeks. Just pulling this in once our CI checks finish. |
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This PR reflect initial implementations of some models we will be adding to KerasHub. Work will be ongoing, but we are moving this to the
masterbranch, as we just cut the final release of KerasNLP before the consolidation work.