fThDrSrSSKJr SSKJr SSKJrJr \R"\ 5r "SS\\5r S/r g)zTextNet model configuration)PretrainedConfig)logging)BackboneConfigMixin*get_aligned_output_features_output_indicesc V^\rSrSrSrSrSSSSSSS/S S /S QS S S S 4 U4S jjrSrU=r$) TextNetConfigar This is the configuration class to store the configuration of a [`TextNextModel`]. It is used to instantiate a TextNext 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 [czczup/textnet-base](https://huggingface.co/czczup/textnet-base). Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs.Read the documentation from [`PretrainedConfig`] for more information. Args: stem_kernel_size (`int`, *optional*, defaults to 3): The kernel size for the initial convolution layer. stem_stride (`int`, *optional*, defaults to 2): The stride for the initial convolution layer. stem_num_channels (`int`, *optional*, defaults to 3): The num of channels in input for the initial convolution layer. stem_out_channels (`int`, *optional*, defaults to 64): The num of channels in out for the initial convolution layer. stem_act_func (`str`, *optional*, defaults to `"relu"`): The activation function for the initial convolution layer. image_size (`Tuple[int, int]`, *optional*, defaults to `[640, 640]`): The size (resolution) of each image. conv_layer_kernel_sizes (`List[List[List[int]]]`, *optional*): A list of stage-wise kernel sizes. If `None`, defaults to: `[[[3, 3], [3, 3], [3, 3]], [[3, 3], [1, 3], [3, 3], [3, 1]], [[3, 3], [3, 3], [3, 1], [1, 3]], [[3, 3], [3, 1], [1, 3], [3, 3]]]`. conv_layer_strides (`List[List[int]]`, *optional*): A list of stage-wise strides. If `None`, defaults to: `[[1, 2, 1], [2, 1, 1, 1], [2, 1, 1, 1], [2, 1, 1, 1]]`. hidden_sizes (`List[int]`, *optional*, defaults to `[64, 64, 128, 256, 512]`): Dimensionality (hidden size) at each stage. batch_norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the batch normalization layers. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. out_features (`List[str]`, *optional*): If used as backbone, list of features to output. Can be any of `"stem"`, `"stage1"`, `"stage2"`, etc. (depending on how many stages the model has). If unset and `out_indices` is set, will default to the corresponding stages. If unset and `out_indices` is unset, will default to the last stage. out_indices (`List[int]`, *optional*): If used as backbone, list of indices of features to output. Can be any of 0, 1, 2, etc. (depending on how many stages the model has). If unset and `out_features` is set, will default to the corresponding stages. If unset and `out_features` is unset, will default to the last stage. Examples: ```python >>> from transformers import TextNetConfig, TextNetBackbone >>> # Initializing a TextNetConfig >>> configuration = TextNetConfig() >>> # Initializing a model (with random weights) >>> model = TextNetBackbone(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```textnet@reluiN)r r igh㈵>g{Gz?c 6>[TU]"S 0UD6 Uc3SS/SS/SS//SS/SS/SS/SS//SS/SS/SS/SS//SS/SS/SS/SS///nUc/SQ/SQ/SQ/SQ/nXlX lX0lX@lXPlX`lXplXl Xl Xl Xl URVs/sHn[U5PM snUlS/[SS5Vs/sHnSU3PM sn-Ul[#XUR S9uUlUlgs snfs snf) Nr )rr r)r rrrstemstage) out_features out_indices stage_names)super__init__stem_kernel_size stem_stridestem_num_channelsstem_out_channels stem_act_func image_sizeconv_layer_kernel_sizesconv_layer_stridesinitializer_range hidden_sizesbatch_norm_epslendepthsrangerr _out_features _out_indices)selfrrrrr r!r"r#r%r&r$rrkwargslayeridx __class__s i/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/textnet/configuration_textnet.pyrTextNetConfig.__init__UsZ" "6" " *Q!Q!Q(Q!Q!Q!Q0Q!Q!Q!Q0Q!Q!Q!Q0 ' #  %"+\<!V  0&!2!2*$'>$"4!2(,/3/K/KL/Kes5z/KL "8a &L se} &LL0Z%DL\L\1 -D-M&Ls )DD)r*r+r&r"r#r(r%r!r$rr rrrr) __name__ __module__ __qualname____firstlineno____doc__ model_typer__static_attributes__ __classcell__)r0s@r1rrsG7 rJ: $,/ / rN) r7 transformersrtransformers.utilsr!transformers.utils.backbone_utilsrr get_loggerr3loggerr__all__rr;r1rBsB")&m   H %k ')9k \  r;