U 9%e9@sdZddlmZddlmZddlmZddlmZddl m Z ddl m Z dd l mZmZe eZd d iZGd d d eeZGddde ZdS)z ConvNeXT model configuration OrderedDict)Mapping)version)PretrainedConfig) OnnxConfig)logging)BackboneConfigMixin*get_aligned_output_features_output_indiceszfacebook/convnext-tiny-224zJhttps://huggingface.co/facebook/convnext-tiny-224/resolve/main/config.jsonc s&eZdZdZdZdfd d ZZS)ConvNextConfigaH This is the configuration class to store the configuration of a [`ConvNextModel`]. It is used to instantiate an ConvNeXT 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 ConvNeXT [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-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: num_channels (`int`, *optional*, defaults to 3): The number of input channels. patch_size (`int`, optional, defaults to 4): Patch size to use in the patch embedding layer. num_stages (`int`, optional, defaults to 4): The number of stages in the model. hidden_sizes (`List[int]`, *optional*, defaults to [96, 192, 384, 768]): Dimensionality (hidden size) at each stage. depths (`List[int]`, *optional*, defaults to [3, 3, 9, 3]): Depth (number of blocks) for each stage. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in each block. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` are supported. 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-12): The epsilon used by the layer normalization layers. layer_scale_init_value (`float`, *optional*, defaults to 1e-6): The initial value for the layer scale. drop_path_rate (`float`, *optional*, defaults to 0.0): The drop rate for stochastic depth. 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. Example: ```python >>> from transformers import ConvNextConfig, ConvNextModel >>> # Initializing a ConvNext convnext-tiny-224 style configuration >>> configuration = ConvNextConfig() >>> # Initializing a model (with random weights) from the convnext-tiny-224 style configuration >>> model = ConvNextModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```ZconvnextrNgelu{Gz?-q=ư>c stjf|||_||_||_|dkr4ddddgn||_|dkrNddddgn||_||_||_||_ | |_ | |_ | |_ dgdd t d t|jd D|_t| | |jd \|_|_dS) N`iir stemcSsg|]}d|qS)Zstage).0idxrrr/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/transformers/models/convnext/configuration_convnext.py zsz+ConvNextConfig.__init__..) out_features out_indices stage_names)super__init__ num_channels patch_size num_stages hidden_sizesdepths hidden_actinitializer_rangelayer_norm_epslayer_scale_init_valuedrop_path_rate image_sizerangelenr r Z _out_featuresZ _out_indices)selfr#r$r%r&r'r(r)r*r+r,r-rrkwargs __class__rrr"\s$&zConvNextConfig.__init__) rr r NNrrrrrrNN)__name__ __module__ __qualname____doc__Z model_typer" __classcell__rrr2rr $s 5r c@sJeZdZedZeeeee effdddZ ee dddZ dS)ConvNextOnnxConfigz1.11)returncCstddddddfgS)NZ pixel_valuesbatchr#heightwidth)rrrrr0rrrinputsszConvNextOnnxConfig.inputscCsdS)Ngh㈵>rr?rrratol_for_validationsz&ConvNextOnnxConfig.atol_for_validationN) r4r5r6rparseZtorch_onnx_minimum_versionpropertyrstrintr@floatrArrrrr9s   r9N)r7 collectionsrtypingr packagingrZconfiguration_utilsrZonnxrutilsr Zutils.backbone_utilsr r Z get_loggerr4loggerZ&CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAPr r9rrrrs       \