fThSrSSKJr SSKJr SSKJr SSKJr SSK J r SSK J r \ R"\5r"S S \5r"S S \ 5rS S /rg )zMobileViTV2 model configuration OrderedDict)Mapping)version)PretrainedConfig) OnnxConfig)loggingch^\rSrSrSrSrSSSSSSS S S S S /SQS S/SQ/SQSSSS4U4SjjrSrU=r$)MobileViTV2Configa This is the configuration class to store the configuration of a [`MobileViTV2Model`]. It is used to instantiate a MobileViTV2 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 MobileViTV2 [apple/mobilevitv2-1.0](https://huggingface.co/apple/mobilevitv2-1.0) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: num_channels (`int`, *optional*, defaults to 3): The number of input channels. image_size (`int`, *optional*, defaults to 256): The size (resolution) of each image. patch_size (`int`, *optional*, defaults to 2): The size (resolution) of each patch. expand_ratio (`float`, *optional*, defaults to 2.0): Expansion factor for the MobileNetv2 layers. hidden_act (`str` or `function`, *optional*, defaults to `"swish"`): The non-linear activation function (function or string) in the Transformer encoder and convolution layers. conv_kernel_size (`int`, *optional*, defaults to 3): The size of the convolutional kernel in the MobileViTV2 layer. output_stride (`int`, *optional*, defaults to 32): The ratio of the spatial resolution of the output to the resolution of the input image. classifier_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout ratio for attached classifiers. 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-05): The epsilon used by the layer normalization layers. aspp_out_channels (`int`, *optional*, defaults to 512): Number of output channels used in the ASPP layer for semantic segmentation. atrous_rates (`List[int]`, *optional*, defaults to `[6, 12, 18]`): Dilation (atrous) factors used in the ASPP layer for semantic segmentation. aspp_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout ratio for the ASPP layer for semantic segmentation. semantic_loss_ignore_index (`int`, *optional*, defaults to 255): The index that is ignored by the loss function of the semantic segmentation model. n_attn_blocks (`List[int]`, *optional*, defaults to `[2, 4, 3]`): The number of attention blocks in each MobileViTV2Layer base_attn_unit_dims (`List[int]`, *optional*, defaults to `[128, 192, 256]`): The base multiplier for dimensions of attention blocks in each MobileViTV2Layer width_multiplier (`float`, *optional*, defaults to 1.0): The width multiplier for MobileViTV2. ffn_multiplier (`int`, *optional*, defaults to 2): The FFN multiplier for MobileViTV2. attn_dropout (`float`, *optional*, defaults to 0.0): The dropout in the attention layer. ffn_dropout (`float`, *optional*, defaults to 0.0): The dropout between FFN layers. Example: ```python >>> from transformers import MobileViTV2Config, MobileViTV2Model >>> # Initializing a mobilevitv2-small style configuration >>> configuration = MobileViTV2Config() >>> # Initializing a model from the mobilevitv2-small style configuration >>> model = MobileViTV2Model(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` mobilevitv2rg@swish g?g{Gz?gh㈵>i) )rr)rg?gc >[TU]"S0UD6 XlX lX0lX@lXPlX`lXplXl Xl Xl UUl UUl UUlUUlUUlXlXlXlXlXlg)N)super__init__ num_channels image_size patch_size expand_ratio hidden_actconv_kernel_size output_strideinitializer_rangelayer_norm_eps n_attn_blocksbase_attn_unit_dimswidth_multiplierffn_multiplier ffn_dropout attn_dropoutclassifier_dropout_probaspp_out_channels atrous_ratesaspp_dropout_probsemantic_loss_ignore_index)selfrrr r!r"r#r$r-r%r&r.r/r0r1r'r(r)r*r,r+kwargs __class__s q/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/mobilevitv2/configuration_mobilevitv2.pyrMobileViTV2Config.__init__cs0 "6"($$($ 0*!2,*#6 0,&('>$"3(!2*D')r0r.r/r,r(r-r#r!r+r*r"rr%r&r'rr$r r1r)) __name__ __module__ __qualname____firstlineno____doc__ model_typer__static_attributes__ __classcell__)r4s@r5r r s[@ DJ # #&++/E/Er7r c\rSrSr\R "S5r\S\\ \\ \ 444Sj5r \S\\ \\ \ 444Sj5r \S\ 4Sj5rSrg) MobileViTV2OnnxConfigz1.11returnc([SSSSSS.4/5$)N pixel_valuesbatchrheightwidth)rrrrr2s r5inputsMobileViTV2OnnxConfig.inputss ^^PX]d-efghhr7clURS:Xa[SSS04/5$[SSS04SSS04/5$)Nzimage-classificationlogitsrrFlast_hidden_state pooler_output)taskrrJs r5outputsMobileViTV2OnnxConfig.outputssL 99. .Aw< 89: :!4q'l CoXY[bWcEdef fr7cg)Ng-C6?rrJs r5atol_for_validation)MobileViTV2OnnxConfig.atol_for_validationsr7rN)r8r9r:r;rparsetorch_onnx_minimum_versionpropertyrstrintrKrRfloatrUr>rr7r5rArAs!(v!6 iWS#X%6 67iiggc3h&7!78gg Ur7rAN)r< collectionsrtypingr packagingrconfiguration_utilsronnxr utilsr get_loggerr8loggerr rA__all__rr7r5rfsY&#3   H %tE(tEnJ&  7 8r7