g}pdZddlmZddlmZddlmZmZeje Z GddeeZ dS)zBiT model configuration)PretrainedConfig)logging)BackboneConfigMixin*get_aligned_output_features_output_indicesc\eZdZdZdZddgZddgZddgd gd dd d d ddd dd d ffd ZxZS) BitConfiga This is the configuration class to store the configuration of a [`BitModel`]. It is used to instantiate an BiT 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 BiT [google/bit-50](https://huggingface.co/google/bit-50) 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. embedding_size (`int`, *optional*, defaults to 64): Dimensionality (hidden size) for the embedding layer. hidden_sizes (`List[int]`, *optional*, defaults to `[256, 512, 1024, 2048]`): Dimensionality (hidden size) at each stage. depths (`List[int]`, *optional*, defaults to `[3, 4, 6, 3]`): Depth (number of layers) for each stage. layer_type (`str`, *optional*, defaults to `"preactivation"`): The layer to use, it can be either `"preactivation"` or `"bottleneck"`. hidden_act (`str`, *optional*, defaults to `"relu"`): The non-linear activation function in each block. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` are supported. global_padding (`str`, *optional*): Padding strategy to use for the convolutional layers. Can be either `"valid"`, `"same"`, or `None`. num_groups (`int`, *optional*, defaults to 32): Number of groups used for the `BitGroupNormActivation` layers. drop_path_rate (`float`, *optional*, defaults to 0.0): The drop path rate for the stochastic depth. embedding_dynamic_padding (`bool`, *optional*, defaults to `False`): Whether or not to make use of dynamic padding for the embedding layer. output_stride (`int`, *optional*, defaults to 32): The output stride of the model. width_factor (`int`, *optional*, defaults to 1): The width factor for the model. 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. Must be in the same order as defined in the `stage_names` attribute. 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. Must be in the same order as defined in the `stage_names` attribute. Example: ```python >>> from transformers import BitConfig, BitModel >>> # Initializing a BiT bit-50 style configuration >>> configuration = BitConfig() >>> # Initializing a model (with random weights) from the bit-50 style configuration >>> model = BitModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` bit preactivation bottleneckSAMEVALIDr@)iii)rrreluN gFc tjd i|||jvr-td|dd|j|C||jvr|}ntd|d||_||_||_ ||_ ||_ ||_ ||_ ||_| |_| |_| |_| |_dgdt'dt)|dzDz|_t-| ||j \|_|_dS) Nz layer_type=z is not one of ,zPadding strategy z not supportedstemcg|]}d|S)stage).0idxs e/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/models/bit/configuration_bit.py z&BitConfig.__init__..s&Z&Z&Z}s}}&Z&Z&Zr) out_features out_indices stage_namesr)super__init__ layer_types ValueErrorjoinuppersupported_padding num_channelsembedding_size hidden_sizesdepths layer_type hidden_actglobal_padding num_groupsdrop_path_rateembedding_dynamic_padding output_stride width_factorrangelenr"r _out_features _out_indices)selfr*r+r,r-r.r/r0r1r2r3r4r5r r!kwargs __class__s rr$zBitConfig.__init__[si$ ""6""" T- - -b:bbchhtO_F`F`bbcc c  %##%%)???!/!5!5!7!7 !S^!S!S!STTT(,( $$,$,)B&*("8&Z&ZaVWX@Y@Y&Z&Z&ZZ0Z%;DL\1 1 1 -D---r) __name__ __module__ __qualname____doc__ model_typer%r)r$ __classcell__)r<s@rrrs;;zJ"L1K)+++||""'* * * * * * * * * * rrN) r@configuration_utilsrutilsrutils.backbone_utilsrr get_loggerr=loggerrrrrrHs333333cccccccc  H % %l l l l l #%5l l l l l r