Fix timm conversion for resnet #1814
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* Add VGG16 backbone (#1737) * 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 `ResNetBackbone` and `ResNetImageClassifier` (#1765) * Add ResNetV1 and ResNetV2 * Address comments * Add CSP DarkNet backbone and classifier (#1774) * Add CSP DarkNet * Add CSP DarkNet * snake_case function names * change use_depthwise to block_type * Add `FeaturePyramidBackbone` and port weights from `timm` for `ResNetBackbone` (#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 (#1775) * Add DenseNet * fix testcase * address comments * nit * fix lint errors * move description * Add ViTDetBackbone (#1776) * 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 Mix transformer (#1780) * Add MixTransformer * fix testcase * test changes and comments * lint fix * update config list * modify testcase for 2 layers * update input_image_shape -> image_shape (#1785) * update input_image_shape -> image_shape * update docstring example * code reformat * update tests * Create __init__.py (#1788) add missing __init__ file to vit_det * Hack package build script to rename to keras-hub (#1793) 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 CLIP and T5XXL for StableDiffusionV3 (#1790) * 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` * Add Bounding Box Utils (#1791) * 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 (#1782) * 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> * Pkgoogle/efficient net migration (#1778) * 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 the ResNet_vd backbone (#1766) * Add ResNet_vd to ResNet backbone * Addressed requested parameter changes * Fixed tests and updated comments * Added new parameters to docstring * Add `VAEImageDecoder` for StableDiffusionV3 (#1796) * Add `VAEImageDecoder` for StableDiffusionV3 * Use `keras.Model` for `VAEImageDecoder` and follows the coding style in `VAEAttention` * Replace `Backbone` with `keras.Model` in `CLIPTextEncoder` and `T5XXLTextEncoder` (#1802) * Add pyramid output for densenet, cspDarknet (#1801) * 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 `MMDiT` for StableDiffusionV3 (#1806) * Add `MMDiT` * Update * Update * Update implementation * Add remaining bbox utils (#1804) * - 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 * Fix timm conversion for rersnet (#1814) * Add `StableDiffusion3` * Fix `_normalize_inputs` * Separate CLIP encoders from SD3 backbone. * Simplify `text_to_image` function. * Address comments * Minor update and add docstrings. * Add VGG16 backbone (#1737) * 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 `ResNetBackbone` and `ResNetImageClassifier` (#1765) * Add ResNetV1 and ResNetV2 * Address comments * Add CSP DarkNet backbone and classifier (#1774) * Add CSP DarkNet * Add CSP DarkNet * snake_case function names * change use_depthwise to block_type * Add `FeaturePyramidBackbone` and port weights from `timm` for `ResNetBackbone` (#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 (#1775) * Add DenseNet * fix testcase * address comments * nit * fix lint errors * move description * Add ViTDetBackbone (#1776) * 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 Mix transformer (#1780) * Add MixTransformer * fix testcase * test changes and comments * lint fix * update config list * modify testcase for 2 layers * update input_image_shape -> image_shape (#1785) * update input_image_shape -> image_shape * update docstring example * code reformat * update tests * Create __init__.py (#1788) add missing __init__ file to vit_det * Hack package build script to rename to keras-hub (#1793) 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 CLIP and T5XXL for StableDiffusionV3 (#1790) * 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` * Add Bounding Box Utils (#1791) * 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 (#1782) * 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> * Pkgoogle/efficient net migration (#1778) * 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 the ResNet_vd backbone (#1766) * Add ResNet_vd to ResNet backbone * Addressed requested parameter changes * Fixed tests and updated comments * Added new parameters to docstring * Add `VAEImageDecoder` for StableDiffusionV3 (#1796) * Add `VAEImageDecoder` for StableDiffusionV3 * Use `keras.Model` for `VAEImageDecoder` and follows the coding style in `VAEAttention` * Replace `Backbone` with `keras.Model` in `CLIPTextEncoder` and `T5XXLTextEncoder` (#1802) * Add pyramid output for densenet, cspDarknet (#1801) * 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 `MMDiT` for StableDiffusionV3 (#1806) * Add `MMDiT` * Update * Update * Update implementation * Add remaining bbox utils (#1804) * - 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 * Fix timm conversion for rersnet (#1814) * Fix * Update * Rename to diffuser and decoder * Define functional model * Merge from upstream/master * Delete old SD3 * Fix copyright * Rename to keras_hub * Address comments * Update * Fix CI * Fix bugs occurred in keras3.1 --------- Co-authored-by: Divyashree Sreepathihalli <divyashreepathihalli@gmail.com> Co-authored-by: Sachin Prasad <sachinprasad@google.com> Co-authored-by: Matt Watson <1389937+mattdangerw@users.noreply.github.com> Co-authored-by: Siva Sravana Kumar Neeli <113718461+sineeli@users.noreply.github.com> Co-authored-by: Usha Rengaraju <34335028+ushareng@users.noreply.github.com> Co-authored-by: ushareng <usha.rengaraju@gmail.com> Co-authored-by: pkgoogle <132095473+pkgoogle@users.noreply.github.com> Co-authored-by: gowthamkpr <47574994+gowthamkpr@users.noreply.github.com>
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This is with the recent changes with resnet_vd which is breaking the timm conversion for resnet.
This fixes the naming convention with the latest changes and adds new arguments.