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merged 7 commits into from
Sep 3, 2024

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@sachinprasadhs sachinprasadhs commented Aug 27, 2024

  • Change from Backbone class to FeaturePyramidBackbone to get pyramid outputs for DenseNet and CSPdarkNet
  • Make common test case for pyramid outputs.

@sachinprasadhs sachinprasadhs changed the title Add pyramid output for densenet. Add pyramid output for densenet, cspDarknet Aug 28, 2024
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Just a couple comments.

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Thanks! A few more comments on the test case work.

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LGTM! Thanks!

@mattdangerw mattdangerw merged commit 9143468 into keras-team:keras-hub Sep 3, 2024
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@sachinprasadhs sachinprasadhs deleted the densenet_fp branch September 5, 2024 20:39
mattdangerw pushed a commit to mattdangerw/keras-hub that referenced this pull request Sep 10, 2024
* 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
mattdangerw pushed a commit that referenced this pull request Sep 11, 2024
* 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
mattdangerw pushed a commit that referenced this pull request Sep 13, 2024
* 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
mattdangerw pushed a commit that referenced this pull request Sep 17, 2024
* 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
divyashreepathihalli added a commit that referenced this pull request Sep 25, 2024
* 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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