U Ö9%e2ã@sBdZddlmZddlmZe e¡ZddiZGdd„deƒZ dS) z( Swin2SR Transformer model configurationé)ÚPretrainedConfig)Úloggingz caidas/swin2sr-classicalsr-x2-64zPhttps://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.jsoncsreZdZdZdZddddœZddd d d d d d d d gd d d d d d gd d ddddddddddddf‡fdd„ Z‡ZS)Ú Swin2SRConfigao This is the configuration class to store the configuration of a [`Swin2SRModel`]. It is used to instantiate a Swin Transformer v2 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 Swin Transformer v2 [caidas/swin2sr-classicalsr-x2-64](https://huggingface.co/caidas/swin2sr-classicalsr-x2-64) 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 64): The size (resolution) of each image. patch_size (`int`, *optional*, defaults to 1): The size (resolution) of each patch. num_channels (`int`, *optional*, defaults to 3): The number of input channels. embed_dim (`int`, *optional*, defaults to 180): Dimensionality of patch embedding. depths (`list(int)`, *optional*, defaults to `[6, 6, 6, 6, 6, 6]`): Depth of each layer in the Transformer encoder. num_heads (`list(int)`, *optional*, defaults to `[6, 6, 6, 6, 6, 6]`): Number of attention heads in each layer of the Transformer encoder. window_size (`int`, *optional*, defaults to 8): Size of windows. mlp_ratio (`float`, *optional*, defaults to 2.0): Ratio of MLP hidden dimensionality to embedding dimensionality. qkv_bias (`bool`, *optional*, defaults to `True`): Whether or not a learnable bias should be added to the queries, keys and values. hidden_dropout_prob (`float`, *optional*, defaults to 0.0): The dropout probability for all fully connected layers in the embeddings and encoder. attention_probs_dropout_prob (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. drop_path_rate (`float`, *optional*, defaults to 0.1): Stochastic depth rate. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` are supported. use_absolute_embeddings (`bool`, *optional*, defaults to `False`): Whether or not to add absolute position embeddings to the patch embeddings. 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. upscale (`int`, *optional*, defaults to 2): The upscale factor for the image. 2/3/4/8 for image super resolution, 1 for denoising and compress artifact reduction img_range (`float`, *optional*, defaults to 1.): The range of the values of the input image. resi_connection (`str`, *optional*, defaults to `"1conv"`): The convolutional block to use before the residual connection in each stage. upsampler (`str`, *optional*, defaults to `"pixelshuffle"`): The reconstruction reconstruction module. Can be 'pixelshuffle'/'pixelshuffledirect'/'nearest+conv'/None. Example: ```python >>> from transformers import Swin2SRConfig, Swin2SRModel >>> # Initializing a Swin2SR caidas/swin2sr-classicalsr-x2-64 style configuration >>> configuration = Swin2SRConfig() >>> # Initializing a model (with random weights) from the caidas/swin2sr-classicalsr-x2-64 style configuration >>> model = Swin2SRModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```Zswin2srÚ embed_dimÚ num_headsÚ num_layers)Z hidden_sizeZnum_attention_headsZnum_hidden_layersé@éré´éég@Tggš™™™™™¹?ZgeluFg{®Gáz”?gñh㈵øä>égð?Z1convZ pixelshufflec s”tƒjf|Ž||_||_||_||_||_t|ƒ|_||_ ||_ ||_ | |_ | |_ | |_| |_| |_||_||_||_||_||_||_||_dS)N)ÚsuperÚ__init__Ú image_sizeÚ patch_sizeÚ num_channelsrÚdepthsÚlenrrÚ window_sizeÚ mlp_ratioÚqkv_biasÚhidden_dropout_probÚattention_probs_dropout_probÚdrop_path_rateÚ hidden_actÚuse_absolute_embeddingsÚlayer_norm_epsÚinitializer_rangeÚupscaleÚ img_rangeÚresi_connectionÚ upsampler)Úselfrrrrrrrrrrrrrrrrrr r!r"Úkwargs©Ú __class__©úp/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/transformers/models/swin2sr/configuration_swin2sr.pyrjs, zSwin2SRConfig.__init__)Ú__name__Ú __module__Ú __qualname__Ú__doc__Z model_typeZ attribute_maprÚ __classcell__r'r'r%r(rs6CýërN) r,Zconfiguration_utilsrÚutilsrZ get_loggerr)ÚloggerZ%SWIN2SR_PRETRAINED_CONFIG_ARCHIVE_MAPrr'r'r'r(Ús   þ