transformers/docs/source/model_doc/auto.mdx
Yih-Dar b67fd797be
Add TFVisionEncoderDecoderModel (#14148)
* Start the work on TFVisionEncoderDecoderModel

* Expose TFVisionEncoderDecoderModel

* fix import

* Add modeling_tf_vision_encoder_decoder to _ignore_modules in get_model_modules()

* reorder

* Apply the fix for checkpoint loading as in #14016

* remove attention_mask + fix VISION_DUMMY_INPUTS

* A minimal change to make TF generate() work for vision models as encoder in encoder-decoder setting

* fix wrong condition: shape_list(input_ids) == 2

* add tests

* use personal TFViTModel checkpoint (for now)

* Add equivalence tests + projection layer

* style

* make sure projection layer can run

* Add examples

* Apply suggestions from code review

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

* Clean comments (need to work on TODOs for PyTorch models)

* Remove TF -> PT in check_pt_tf_equivalence for TFVisionEncoderDecoderModel

* fixes

* Revert changes in PT code.

* Update tests/test_modeling_tf_vision_encoder_decoder.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add test_inference_coco_en for TF test

* fix quality

* fix name

* build doc

* add main_input_name

* Fix ckpt name in test

* fix diff between master and this PR

* fix doc

* fix style and quality

* fix missing doc

* fix labels handling

* Delete auto.rst

* Add the changes done in #14016

* fix prefix

* Apply suggestions from code review

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

* make style

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
2022-01-10 13:30:14 -05:00

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# Auto Classes
In many cases, the architecture you want to use can be guessed from the name or the path of the pretrained model you
are supplying to the `from_pretrained()` method. AutoClasses are here to do this job for you so that you
automatically retrieve the relevant model given the name/path to the pretrained weights/config/vocabulary.
Instantiating one of [`AutoConfig`], [`AutoModel`], and
[`AutoTokenizer`] will directly create a class of the relevant architecture. For instance
```python
model = AutoModel.from_pretrained("bert-base-cased")
```
will create a model that is an instance of [`BertModel`].
There is one class of `AutoModel` for each task, and for each backend (PyTorch, TensorFlow, or Flax).
## Extending the Auto Classes
Each of the auto classes has a method to be extended with your custom classes. For instance, if you have defined a
custom class of model `NewModel`, make sure you have a `NewModelConfig` then you can add those to the auto
classes like this:
```python
from transformers import AutoConfig, AutoModel
AutoConfig.register("new-model", NewModelConfig)
AutoModel.register(NewModelConfig, NewModel)
```
You will then be able to use the auto classes like you would usually do!
<Tip warning={true}>
If your `NewModelConfig` is a subclass of [`~transformer.PretrainedConfig`], make sure its
`model_type` attribute is set to the same key you use when registering the config (here `"new-model"`).
Likewise, if your `NewModel` is a subclass of [`PreTrainedModel`], make sure its
`config_class` attribute is set to the same class you use when registering the model (here
`NewModelConfig`).
</Tip>
## AutoConfig
[[autodoc]] AutoConfig
## AutoTokenizer
[[autodoc]] AutoTokenizer
## AutoFeatureExtractor
[[autodoc]] AutoFeatureExtractor
## AutoProcessor
[[autodoc]] AutoProcessor
## AutoModel
[[autodoc]] AutoModel
## AutoModelForPreTraining
[[autodoc]] AutoModelForPreTraining
## AutoModelForCausalLM
[[autodoc]] AutoModelForCausalLM
## AutoModelForMaskedLM
[[autodoc]] AutoModelForMaskedLM
## AutoModelForSeq2SeqLM
[[autodoc]] AutoModelForSeq2SeqLM
## AutoModelForSequenceClassification
[[autodoc]] AutoModelForSequenceClassification
## AutoModelForMultipleChoice
[[autodoc]] AutoModelForMultipleChoice
## AutoModelForNextSentencePrediction
[[autodoc]] AutoModelForNextSentencePrediction
## AutoModelForTokenClassification
[[autodoc]] AutoModelForTokenClassification
## AutoModelForQuestionAnswering
[[autodoc]] AutoModelForQuestionAnswering
## AutoModelForTableQuestionAnswering
[[autodoc]] AutoModelForTableQuestionAnswering
## AutoModelForImageClassification
[[autodoc]] AutoModelForImageClassification
## AutoModelForVision2Seq
[[autodoc]] AutoModelForVision2Seq
## AutoModelForAudioClassification
[[autodoc]] AutoModelForAudioClassification
## AutoModelForAudioFrameClassification
[[autodoc]] AutoModelForAudioFrameClassification
## AutoModelForCTC
[[autodoc]] AutoModelForCTC
## AutoModelForSpeechSeq2Seq
[[autodoc]] AutoModelForSpeechSeq2Seq
## AutoModelForAudioXVector
[[autodoc]] AutoModelForAudioXVector
## AutoModelForObjectDetection
[[autodoc]] AutoModelForObjectDetection
## AutoModelForImageSegmentation
[[autodoc]] AutoModelForImageSegmentation
## TFAutoModel
[[autodoc]] TFAutoModel
## TFAutoModelForPreTraining
[[autodoc]] TFAutoModelForPreTraining
## TFAutoModelForCausalLM
[[autodoc]] TFAutoModelForCausalLM
## TFAutoModelForImageClassification
[[autodoc]] TFAutoModelForImageClassification
## TFAutoModelForMaskedLM
[[autodoc]] TFAutoModelForMaskedLM
## TFAutoModelForSeq2SeqLM
[[autodoc]] TFAutoModelForSeq2SeqLM
## TFAutoModelForSequenceClassification
[[autodoc]] TFAutoModelForSequenceClassification
## TFAutoModelForMultipleChoice
[[autodoc]] TFAutoModelForMultipleChoice
## TFAutoModelForTableQuestionAnswering
[[autodoc]] TFAutoModelForTableQuestionAnswering
## TFAutoModelForTokenClassification
[[autodoc]] TFAutoModelForTokenClassification
## TFAutoModelForQuestionAnswering
[[autodoc]] TFAutoModelForQuestionAnswering
## TFAutoModelForVision2Seq
[[autodoc]] TFAutoModelForVision2Seq
## FlaxAutoModel
[[autodoc]] FlaxAutoModel
## FlaxAutoModelForCausalLM
[[autodoc]] FlaxAutoModelForCausalLM
## FlaxAutoModelForPreTraining
[[autodoc]] FlaxAutoModelForPreTraining
## FlaxAutoModelForMaskedLM
[[autodoc]] FlaxAutoModelForMaskedLM
## FlaxAutoModelForSeq2SeqLM
[[autodoc]] FlaxAutoModelForSeq2SeqLM
## FlaxAutoModelForSequenceClassification
[[autodoc]] FlaxAutoModelForSequenceClassification
## FlaxAutoModelForQuestionAnswering
[[autodoc]] FlaxAutoModelForQuestionAnswering
## FlaxAutoModelForTokenClassification
[[autodoc]] FlaxAutoModelForTokenClassification
## FlaxAutoModelForMultipleChoice
[[autodoc]] FlaxAutoModelForMultipleChoice
## FlaxAutoModelForNextSentencePrediction
[[autodoc]] FlaxAutoModelForNextSentencePrediction
## FlaxAutoModelForImageClassification
[[autodoc]] FlaxAutoModelForImageClassification
## FlaxAutoModelForVision2Seq
[[autodoc]] FlaxAutoModelForVision2Seq