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Add checkpoint links in a few config classes (#19910)

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* For CLIP

* Others

* update

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2022-10-27 09:26:10 +02:00
committed by GitHub
parent 7629656926
commit 803475fb69
5 changed files with 9 additions and 7 deletions
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4
src/transformers/models/clip/configuration_clip.py
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@@ -254,7 +254,9 @@ class CLIPVisionConfig(PretrainedConfig):
class CLIPConfig(PretrainedConfig): class CLIPConfig(PretrainedConfig):
r""" r"""
[`CLIPConfig`] is the configuration class to store the configuration of a [`CLIPModel`]. It is used to instantiate [`CLIPConfig`] is the configuration class to store the configuration of a [`CLIPModel`]. It is used to instantiate
CLIP model according to the specified arguments, defining the text model and vision model configs. CLIP model according to the specified arguments, defining the text model and vision model configs. Instantiating a
configuration with the defaults will yield a similar configuration to that of the CLIP
[openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) architecture.
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information. documentation from [`PretrainedConfig`] for more information.

3
src/transformers/models/groupvit/configuration_groupvit.py
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@@ -273,7 +273,8 @@ class GroupViTConfig(PretrainedConfig):
r""" r"""
[`GroupViTConfig`] is the configuration class to store the configuration of a [`GroupViTModel`]. It is used to [`GroupViTConfig`] is the configuration class to store the configuration of a [`GroupViTModel`]. It is used to
instantiate a GroupViT model according to the specified arguments, defining the text model and vision model instantiate a GroupViT model according to the specified arguments, defining the text model and vision model
configs. configs. Instantiating a configuration with the defaults will yield a similar configuration to that of the GroupViT
[nvidia/groupvit-gcc-yfcc](https://huggingface.co/nvidia/groupvit-gcc-yfcc) architecture.
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information. documentation from [`PretrainedConfig`] for more information.

3
src/transformers/models/owlvit/configuration_owlvit.py
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@@ -253,7 +253,8 @@ class OwlViTConfig(PretrainedConfig):
r""" r"""
[`OwlViTConfig`] is the configuration class to store the configuration of an [`OwlViTModel`]. It is used to [`OwlViTConfig`] is the configuration class to store the configuration of an [`OwlViTModel`]. It is used to
instantiate an OWL-ViT model according to the specified arguments, defining the text model and vision model instantiate an OWL-ViT model according to the specified arguments, defining the text model and vision model
configs. configs. Instantiating a configuration with the defaults will yield a similar configuration to that of the OWL-ViT
[google/owlvit-base-patch32](https://huggingface.co/google/owlvit-base-patch32) architecture.
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information. documentation from [`PretrainedConfig`] for more information.

2
src/transformers/models/x_clip/configuration_x_clip.py
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@@ -272,6 +272,8 @@ class XCLIPConfig(PretrainedConfig):
r""" r"""
[`XCLIPConfig`] is the configuration class to store the configuration of a [`XCLIPModel`]. It is used to [`XCLIPConfig`] is the configuration class to store the configuration of a [`XCLIPModel`]. It is used to
instantiate X-CLIP model according to the specified arguments, defining the text model and vision model configs. instantiate X-CLIP model according to the specified arguments, defining the text model and vision model configs.
Instantiating a configuration with the defaults will yield a similar configuration to that of the X-CLIP
[microsoft/xclip-base-patch32](https://huggingface.co/microsoft/xclip-base-patch32) architecture.
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information. documentation from [`PretrainedConfig`] for more information.

4
utils/check_config_docstrings.py
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@@ -40,16 +40,12 @@ _re_checkpoint = re.compile("\[(.+?)\]\((https://huggingface\.co/.+?)\)")
CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK = { CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK = {
"CLIPConfig",
"OwlViTConfig",
"GroupViTConfig",
"DecisionTransformerConfig", "DecisionTransformerConfig",
"EncoderDecoderConfig", "EncoderDecoderConfig",
"RagConfig", "RagConfig",
"SpeechEncoderDecoderConfig", "SpeechEncoderDecoderConfig",
"VisionEncoderDecoderConfig", "VisionEncoderDecoderConfig",
"VisionTextDualEncoderConfig", "VisionTextDualEncoderConfig",
"XCLIPConfig",
} }