fThSrSSKJr SSKJr SSKJr SSKJr SSK J r SSK J r \ R"\5r"S S \5r"S S \ 5rS S /rg )zLeViT model configuration OrderedDict)Mapping)version)PretrainedConfig) OnnxConfig)loggingch^\rSrSrSrSrSSSSSS/S Q/S Q/S Q/S QS /SQ/SQS4U4SjjrSrU=r$) LevitConfiga This is the configuration class to store the configuration of a [`LevitModel`]. It is used to instantiate a LeViT model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the LeViT [facebook/levit-128S](https://huggingface.co/facebook/levit-128S) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: image_size (`int`, *optional*, defaults to 224): The size of the input image. num_channels (`int`, *optional*, defaults to 3): Number of channels in the input image. kernel_size (`int`, *optional*, defaults to 3): The kernel size for the initial convolution layers of patch embedding. stride (`int`, *optional*, defaults to 2): The stride size for the initial convolution layers of patch embedding. padding (`int`, *optional*, defaults to 1): The padding size for the initial convolution layers of patch embedding. patch_size (`int`, *optional*, defaults to 16): The patch size for embeddings. hidden_sizes (`List[int]`, *optional*, defaults to `[128, 256, 384]`): Dimension of each of the encoder blocks. num_attention_heads (`List[int]`, *optional*, defaults to `[4, 8, 12]`): Number of attention heads for each attention layer in each block of the Transformer encoder. depths (`List[int]`, *optional*, defaults to `[4, 4, 4]`): The number of layers in each encoder block. key_dim (`List[int]`, *optional*, defaults to `[16, 16, 16]`): The size of key in each of the encoder blocks. drop_path_rate (`int`, *optional*, defaults to 0): The dropout probability for stochastic depths, used in the blocks of the Transformer encoder. mlp_ratios (`List[int]`, *optional*, defaults to `[2, 2, 2]`): Ratio of the size of the hidden layer compared to the size of the input layer of the Mix FFNs in the encoder blocks. attention_ratios (`List[int]`, *optional*, defaults to `[2, 2, 2]`): Ratio of the size of the output dimension compared to input dimension of attention layers. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. Example: ```python >>> from transformers import LevitConfig, LevitModel >>> # Initializing a LeViT levit-128S style configuration >>> configuration = LevitConfig() >>> # Initializing a model (with random weights) from the levit-128S style configuration >>> model = LevitModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```levitr)i) )rrr)rrrr)rrrg{Gz?c (>[TU]"S0UD6 XlX lX0lX@lXPlXplXlXl Xl Xl X`l Xl XlXlSU SUSU S-SSS/SU SUSU S-SSS//Ulg)N Subsamplerrrr)super__init__ image_size num_channels kernel_sizestridepadding hidden_sizesnum_attention_headsdepthskey_dimdrop_path_rate patch_sizeattention_ratio mlp_ratioinitializer_rangedown_ops)selfrrrr r!r'r"r#r$r%r&r)r(r*kwargs __class__s e/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/levit/configuration_levit.pyrLevitConfig.__init__Xs$ "6"$(&  (#6   ,$."!2 '!*l1o&CQ1 M '!*l1o&CQ1 M  )r(r$r+r&r"rr*rr%r)r#rr!r'r ) __name__ __module__ __qualname____firstlineno____doc__ model_typer__static_attributes__ __classcell__)r.s@r/r r sF5 nJ$&!$ $ r1r c|\rSrSr\R "S5r\S\\ \\ \ 444Sj5r \S\ 4Sj5r Srg)LevitOnnxConfigrz1.11returnc([SSSSSS.4/5$)N pixel_valuesbatchrheightwidth)rrrrrr,s r/inputsLevitOnnxConfig.inputss&WHQX!YZ   r1cg)Ng-C6?rrBs r/atol_for_validation#LevitOnnxConfig.atol_for_validationsr1rN)r2r3r4r5rparsetorch_onnx_minimum_versionpropertyrstrintrCfloatrFr8rr1r/r;r;sX!(v!6  WS#X%6 67  Ur1r;N)r6 collectionsrtypingr packagingrconfiguration_utilsronnxr utilsr get_loggerr2loggerr r;__all__rr1r/rWsW #3   H %^ "^ D j  + ,r1