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[docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig (#27128)

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* [docstring] Fix docstring for AltCLIPVisionConfig, AltCLIPTextConfig + cleaned some docstring

* Removed entries from check_docstring.py

* Removed entries from check_docstring.py

* Removed entry from check_docstring.py

* [docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig
This commit is contained in:
Akshar Goyal
2023-10-31 06:20:14 -04:00
committed by GitHub
parent b5c8e23f0f
commit 9234caefb0
10 changed files with 26 additions and 17 deletions
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19
src/transformers/models/altclip/configuration_altclip.py
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@@ -61,12 +61,19 @@ class AltCLIPTextConfig(PretrainedConfig):
max_position_embeddings (`int`, *optional*, defaults to 514):
The maximum sequence length that this model might ever be used with. Typically set this to something large
just in case (e.g., 512 or 1024 or 2048).
type_vocab_size (`int`, *optional*, defaults to 2):
type_vocab_size (`int`, *optional*, defaults to 1):
The vocabulary size of the `token_type_ids` passed when calling [`AltCLIPTextModel`]
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
layer_norm_eps (`float`, *optional*, defaults to 1e-5):
initializer_factor (`float`, *optional*, defaults to 0.02):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
layer_norm_eps (`float`, *optional*, defaults to 1e-05):
The epsilon used by the layer normalization layers.
pad_token_id (`int`, *optional*, defaults to 1): The id of the *padding* token.
bos_token_id (`int`, *optional*, defaults to 0): The id of the *beginning-of-sequence* token.
eos_token_id (`Union[int, List[int]]`, *optional*, defaults to 2):
The id of the *end-of-sequence* token. Optionally, use a list to set multiple *end-of-sequence* tokens.
position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`. For
positional embeddings use `"absolute"`. For more information on `"relative_key"`, please refer to
@@ -154,10 +161,14 @@ class AltCLIPVisionConfig(PretrainedConfig):
Dimensionality of the encoder layers and the pooler layer.
intermediate_size (`int`, *optional*, defaults to 3072):
Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
projection_dim (`int`, *optional*, defaults to 512):
Dimentionality of text and vision projection layers.
num_hidden_layers (`int`, *optional*, defaults to 12):
Number of hidden layers in the Transformer encoder.
num_attention_heads (`int`, *optional*, defaults to 12):
Number of attention heads for each attention layer in the Transformer encoder.
num_channels (`int`, *optional*, defaults to 3):
The number of input channels.
image_size (`int`, *optional*, defaults to 224):
The size (resolution) of each image.
patch_size (`int`, *optional*, defaults to 32):
@@ -165,13 +176,13 @@ class AltCLIPVisionConfig(PretrainedConfig):
hidden_act (`str` or `function`, *optional*, defaults to `"quick_gelu"`):
The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
`"relu"`, `"selu"` and `"gelu_new"` ``"quick_gelu"` are supported.
layer_norm_eps (`float`, *optional*, defaults to 1e-5):
layer_norm_eps (`float`, *optional*, defaults to 1e-05):
The epsilon used by the layer normalization layers.
attention_dropout (`float`, *optional*, defaults to 0.0):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1):
initializer_factor (`float`, *optional*, defaults to 1.0):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).

6
src/transformers/models/bridgetower/configuration_bridgetower.py
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@@ -49,7 +49,7 @@ class BridgeTowerVisionConfig(PretrainedConfig):
The size (resolution) of each patch.
image_size (`int`, *optional*, defaults to 288):
The size (resolution) of each image.
initializer_factor (`float``, *optional*, defaults to 1):
initializer_factor (`float`, *optional*, defaults to 1):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
layer_norm_eps (`float`, *optional*, defaults to 1e-05):
@@ -151,7 +151,7 @@ class BridgeTowerTextConfig(PretrainedConfig):
just in case (e.g., 512 or 1024 or 2048).
type_vocab_size (`int`, *optional*, defaults to 2):
The vocabulary size of the `token_type_ids`.
initializer_factor (`float``, *optional*, defaults to 1):
initializer_factor (`float`, *optional*, defaults to 1):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
layer_norm_eps (`float`, *optional*, defaults to 1e-05):
@@ -255,7 +255,7 @@ class BridgeTowerConfig(PretrainedConfig):
The non-linear activation function (function or string) in the encoder and pooler.
hidden_size (`int`, *optional*, defaults to 768):
Dimensionality of the encoder layers and the pooler layer.
initializer_factor (`float``, *optional*, defaults to 1):
initializer_factor (`float`, *optional*, defaults to 1):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
layer_norm_eps (`float`, *optional*, defaults to 1e-05):

2
src/transformers/models/chinese_clip/configuration_chinese_clip.py
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@@ -203,7 +203,7 @@ class ChineseCLIPVisionConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1.0):
initializer_factor (`float`, *optional*, defaults to 1.0):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
Example:

2
src/transformers/models/clipseg/configuration_clipseg.py
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@@ -62,7 +62,7 @@ class CLIPSegTextConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1.0):
initializer_factor (`float`, *optional*, defaults to 1.0):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
pad_token_id (`int`, *optional*, defaults to 1):

2
src/transformers/models/mask2former/configuration_mask2former.py
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@@ -93,7 +93,7 @@ class Mask2FormerConfig(PretrainedConfig):
Ratio of points that are sampled via importance sampling.
init_std (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
init_xavier_std (`float``, *optional*, defaults to 1.0):
init_xavier_std (`float`, *optional*, defaults to 1.0):
The scaling factor used for the Xavier initialization gain in the HM Attention map module.
use_auxiliary_loss (`boolean``, *optional*, defaults to `True`):
If `True` [`Mask2FormerForUniversalSegmentationOutput`] will contain the auxiliary losses computed using

2
src/transformers/models/owlv2/configuration_owlv2.py
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@@ -180,7 +180,7 @@ class Owlv2VisionConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1.0):
initializer_factor (`float`, *optional*, defaults to 1.0):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).

2
src/transformers/models/owlvit/configuration_owlvit.py
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@@ -183,7 +183,7 @@ class OwlViTVisionConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1.0):
initializer_factor (`float`, *optional*, defaults to 1.0):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).

2
src/transformers/models/pix2struct/configuration_pix2struct.py
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@@ -203,7 +203,7 @@ class Pix2StructVisionConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 1e-10):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1.0):
initializer_factor (`float`, *optional*, defaults to 1.0):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
seq_len (`int`, *optional*, defaults to 4096):

4
src/transformers/models/x_clip/configuration_x_clip.py
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@@ -63,7 +63,7 @@ class XCLIPTextConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1):
initializer_factor (`float`, *optional*, defaults to 1):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
@@ -176,7 +176,7 @@ class XCLIPVisionConfig(PretrainedConfig):
The dropout ratio for the attention probabilities.
initializer_range (`float`, *optional*, defaults to 0.02):
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
initializer_factor (`float``, *optional*, defaults to 1):
initializer_factor (`float`, *optional*, defaults to 1):
A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
testing).
drop_path_rate (`float`, *optional*, defaults to 0.0):

2
utils/check_docstrings.py
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@@ -79,8 +79,6 @@ OBJECTS_TO_IGNORE = [
"AlbertTokenizerFast",
"AlignTextModel",
"AlignVisionConfig",
"AltCLIPTextConfig",
"AltCLIPVisionConfig",
"AudioClassificationPipeline",
"AutoformerConfig",
"AutomaticSpeechRecognitionPipeline",