fTh2SrSSKJr SSKJrJrJr SSKJr SSK J r SSK J r SSK Jr \R"\5r"S S \ 5r"S S \ 5rS S /rg )zPvt model configuration OrderedDict)CallableListMapping)version)PretrainedConfig) OnnxConfig)loggingc%^\rSrSrSrSrSSS/SQ/SQ/S Q/S Q/S Q/S Q/S QS SSSSSSS4S\S\S\S\\S\\S\\S\\S\\S\\S\\S\\ \ 4S\ S\ S \ S!\ S"\ S#\ S$\4$U4S%jjjr S&rU=r$)' PvtConfig aq This is the configuration class to store the configuration of a [`PvtModel`]. It is used to instantiate an Pvt 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 Pvt [Xrenya/pvt-tiny-224](https://huggingface.co/Xrenya/pvt-tiny-224) 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 input image size num_channels (`int`, *optional*, defaults to 3): The number of input channels. num_encoder_blocks (`int`, *optional*, defaults to 4): The number of encoder blocks (i.e. stages in the Mix Transformer encoder). depths (`List[int]`, *optional*, defaults to `[2, 2, 2, 2]`): The number of layers in each encoder block. sequence_reduction_ratios (`List[int]`, *optional*, defaults to `[8, 4, 2, 1]`): Sequence reduction ratios in each encoder block. hidden_sizes (`List[int]`, *optional*, defaults to `[64, 128, 320, 512]`): Dimension of each of the encoder blocks. patch_sizes (`List[int]`, *optional*, defaults to `[4, 2, 2, 2]`): Patch size before each encoder block. strides (`List[int]`, *optional*, defaults to `[4, 2, 2, 2]`): Stride before each encoder block. num_attention_heads (`List[int]`, *optional*, defaults to `[1, 2, 5, 8]`): Number of attention heads for each attention layer in each block of the Transformer encoder. mlp_ratios (`List[int]`, *optional*, defaults to `[8, 8, 4, 4]`): Ratio of the size of the hidden layer compared to the size of the input layer of the Mix FFNs in the encoder blocks. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` are supported. hidden_dropout_prob (`float`, *optional*, defaults to 0.0): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_probs_dropout_prob (`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. drop_path_rate (`float`, *optional*, defaults to 0.0): The dropout probability for stochastic depth, used in the blocks of the Transformer encoder. layer_norm_eps (`float`, *optional*, defaults to 1e-06): The epsilon used by the layer normalization layers. qkv_bias (`bool`, *optional*, defaults to `True`): Whether or not a learnable bias should be added to the queries, keys and values. num_labels ('int', *optional*, defaults to 1000): The number of classes. Example: ```python >>> from transformers import PvtModel, PvtConfig >>> # Initializing a PVT Xrenya/pvt-tiny-224 style configuration >>> configuration = PvtConfig() >>> # Initializing a model from the Xrenya/pvt-tiny-224 style configuration >>> model = PvtModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```pvtr )rrr)rr)@i@i)rrrr)rrr)rrrrgelugg{Gz?gư>Ti image_size num_channelsnum_encoder_blocksdepthssequence_reduction_ratios hidden_sizes patch_sizesstridesnum_attention_heads mlp_ratios hidden_acthidden_dropout_probattention_probs_dropout_probinitializer_rangedrop_path_ratelayer_norm_epsqkv_bias num_labelsc >[TU]"S0UD6 XlX lX0lX@lXPlX`lXplXl Xl Xl Xl Xl XlXlXlUUlUUlUUlg)N)super__init__rrrrrrr r!r#r"r$r%r&r'r(r)r+r*)selfrrrrrrr r!r"r#r$r%r&r'r(r)r*r+kwargs __class__s a/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/pvt/configuration_pvt.pyr/PvtConfig.__init__bs, "6"$("4 )B&(& $#6 $#6 ,H)!2,,$  )r&rr(r$r%rrr'r)r#r"rrr+r r*rr!)__name__ __module__ __qualname____firstlineno____doc__ model_typeintrrstrrfloatboolr/__static_attributes__ __classcell__)r2s@r3rr s)= ~J"#(/;"5!-))5 ,-3%(.1#' # $')!)!)! )! S )! $(9 )!3i)!#Y)!c)!"#Y)!I)!CM*)!#)!',)!!)! !)!"#)!$%)!&')!)!r5rc\rSrSr\R "S5r\S\\ \\ \ 444Sj5r \S\ 4Sj5r \S\ 4Sj5rSrg) PvtOnnxConfigz1.11returnc([SSSSSS.4/5$)N pixel_valuesbatchrheightwidth)rrrr rr0s r3inputsPvtOnnxConfig.inputss&WHQX!YZ   r5cg)Ng-C6?r-rKs r3atol_for_validation!PvtOnnxConfig.atol_for_validationsr5cg)N r-rKs r3default_onnx_opset PvtOnnxConfig.default_onnx_opsetsr5r-N)r6r7r8r9rparsetorch_onnx_minimum_versionpropertyrr=r<rLr>rOrSr@r-r5r3rCrCss!(v!6  WS#X%6 67  UCr5rCN)r: collectionsrtypingrrr packagingrconfiguration_utilsr onnxr utilsr get_loggerr6loggerrrC__all__r-r5r3rasY"#**3   H %k! k!\J(  (r5