* add new model like

* add v1

* v1

* v1

* vision encoder logits match

* v2

* fix

* add docstring

* CI tests pass

* fix tests

* make fixup

* add to `toctree`

* fix processors

* fix processors

* fix doc

* fill title

* add content doc

* remove from tokenization auto

* fix config

* change order

* add `# Copied from`

* few fixes

- add correct license on modeling text
- remove dummy argument

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* replace name

* refactor a bit

* more refactor

* remove unused arg

* make fixup + remove some `# Adapted from ...`

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* more `# Copied from`

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* now `generate` supports no prefix

* remove `FeatureExtractor`

* fix path

* correct dependency

* fix tests

* few fixes

* add integration tests

* add correct conversion script

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add `blip` to tokenization auto

* fix docstrings

* fix test + add image

* remove processor from uncorrect place

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* clean up a bit

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* clean pixel mask

* clean pixel mask

* fix `F`

* Update src/transformers/models/blip/modeling_blip.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fix output

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fix pad token id

* remove `token_type_ids`

* make fixup

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* make fixup

* Apply suggestions from code review

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* add comments

* Update src/transformers/models/blip/modeling_blip.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* remove `token_type_ids`

* make fixup

* better name

* replace with `image_attention_mask`

* refactor

* make fixup

* better docstring

* replace `answer_xx`

* remove ununsed args

* add `labels`

* add `labels`

* fix processing tests

* make fixup

* make fixup

* put correct repo

* remove `pad`

* remove `crop` and `center_crop`

* Update src/transformers/models/blip/image_processing_blip.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fix

* remove `size_divisor`

* fix weights `init`

* remove unneeded functions

* add suggestions

* minor changes

- change slow test output for PT 1.13
- docstring order

* replace `feature_extractor` by `image_processor`

* fix doctests

* fix weight init order + add fp16 slow test

* add `blip` to doctest

* add correct repo name and fix test

* Update src/transformers/models/blip/processing_blip.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fix tests

* use `convert_to_rgb` from `image_transforms`

* make fixup

* fix large loading issue

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
Younes Belkada
2022-12-21 09:39:10 +01:00
committed by GitHub
parent 3be028bc9d
commit 0d284bd574
33 changed files with 5168 additions and 0 deletions

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@@ -498,6 +498,8 @@
title: Audio models
- isExpanded: false
sections:
- local: model_doc/blip
title: BLIP
- local: model_doc/chinese_clip
title: Chinese-CLIP
- local: model_doc/clip

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@@ -64,6 +64,7 @@ The documentation is organized into five sections:
1. **[BiT](model_doc/bit)** (from Google AI) released with the paper [Big Transfer (BiT): General Visual Representation Learning](https://arxiv.org/abs/1912.11370) by Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby.
1. **[Blenderbot](model_doc/blenderbot)** (from Facebook) released with the paper [Recipes for building an open-domain chatbot](https://arxiv.org/abs/2004.13637) by Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M. Smith, Y-Lan Boureau, Jason Weston.
1. **[BlenderbotSmall](model_doc/blenderbot-small)** (from Facebook) released with the paper [Recipes for building an open-domain chatbot](https://arxiv.org/abs/2004.13637) by Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M. Smith, Y-Lan Boureau, Jason Weston.
1. **[BLIP](model_doc/blip)** (from Salesforce) released with the paper [BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation](https://arxiv.org/abs/2201.12086) by Junnan Li, Dongxu Li, Caiming Xiong, Steven Hoi.
1. **[BLOOM](model_doc/bloom)** (from BigScience workshop) released by the [BigScience Workshop](https://bigscience.huggingface.co/).
1. **[BORT](model_doc/bort)** (from Alexa) released with the paper [Optimal Subarchitecture Extraction For BERT](https://arxiv.org/abs/2010.10499) by Adrian de Wynter and Daniel J. Perry.
1. **[ByT5](model_doc/byt5)** (from Google Research) released with the paper [ByT5: Towards a token-free future with pre-trained byte-to-byte models](https://arxiv.org/abs/2105.13626) by Linting Xue, Aditya Barua, Noah Constant, Rami Al-Rfou, Sharan Narang, Mihir Kale, Adam Roberts, Colin Raffel.
@@ -239,6 +240,7 @@ Flax), PyTorch, and/or TensorFlow.
| BiT | ❌ | ❌ | ✅ | ❌ | ❌ |
| Blenderbot | ✅ | ✅ | ✅ | ✅ | ✅ |
| BlenderbotSmall | ✅ | ✅ | ✅ | ✅ | ✅ |
| BLIP | ❌ | ❌ | ✅ | ❌ | ❌ |
| BLOOM | ❌ | ✅ | ✅ | ❌ | ❌ |
| CamemBERT | ✅ | ✅ | ✅ | ✅ | ❌ |
| CANINE | ✅ | ❌ | ✅ | ❌ | ❌ |

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@@ -0,0 +1,92 @@
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
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
http://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.
-->
# BLIP
## Overview
The BLIP model was proposed in [BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation](https://arxiv.org/abs/2201.12086) by Junnan Li, Dongxu Li, Caiming Xiong, Steven Hoi.
BLIP is a model that is able to perform various multi-modal tasks including
- Visual Question Answering
- Image-Text retrieval (Image-text matching)
- Image Captioning
The abstract from the paper is the following:
*Vision-Language Pre-training (VLP) has advanced the performance for many vision-language tasks.
However, most existing pre-trained models only excel in either understanding-based tasks or generation-based tasks. Furthermore, performance improvement has been largely achieved by scaling up the dataset with noisy image-text pairs collected from the web, which is a suboptimal source of supervision. In this paper, we propose BLIP, a new VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP effectively utilizes the noisy web data by bootstrapping the captions, where a captioner generates synthetic captions and a filter removes the noisy ones. We achieve state-of-the-art results on a wide range of vision-language tasks, such as image-text retrieval (+2.7% in average recall@1), image captioning (+2.8% in CIDEr), and VQA (+1.6% in VQA score). BLIP also demonstrates strong generalization ability when directly transferred to videolanguage tasks in a zero-shot manner. Code, models, and datasets are released.*
![BLIP.gif](https://s3.amazonaws.com/moonup/production/uploads/1670928184033-62441d1d9fdefb55a0b7d12c.gif)
This model was contributed by [ybelkada](https://huggingface.co/ybelkada).
The original code can be found [here](https://github.com/salesforce/BLIP).
## BlipConfig
[[autodoc]] BlipConfig
- from_text_vision_configs
## BlipTextConfig
[[autodoc]] BlipTextConfig
## BlipVisionConfig
[[autodoc]] BlipVisionConfig
## BlipProcessor
[[autodoc]] BlipProcessor
## BlipImageProcessor
[[autodoc]] BlipImageProcessor
- preprocess
## BlipModel
[[autodoc]] BlipModel
- forward
- get_text_features
- get_image_features
## BlipTextModel
[[autodoc]] BlipTextModel
- forward
## BlipVisionModel
[[autodoc]] BlipVisionModel
- forward
## BlipForConditionalGeneration
[[autodoc]] BlipForConditionalGeneration
- forward
## BlipForImageTextRetrieval
[[autodoc]] BlipForImageTextRetrieval
- forward
## BlipForQuestionAnswering
[[autodoc]] BlipForQuestionAnswering
- forward