Zj4SrSSKJr SSKJr SSKJrJr \R"\ 5r \"SS9\"SS \555r \"SS9\"S S \555r \"SS9\"S S \555r /SQrg)zCLAP model configuration)strict)PreTrainedConfig)auto_docstringloggingzlaion/clap-htsat-fused) checkpointc:\rSrSr%SrSrSrSr\\ S'Sr \\ S'S r \\ S 'S r \\ S 'S r \\ S 'Sr\\ S'Sr\\-\ S'Sr\\-\ S'Sr\\ S'Sr\\ S'Sr\\ S'Sr\\ S'Sr\\ S'Sr\S-\ S'Sr\S-\ S 'S!r\\\-S-\ S"'S#r\\ S$'S%rg)&ClapTextConfigac Examples: ```python >>> from transformers import ClapTextConfig, ClapTextModel >>> # Initializing a CLAP text configuration >>> configuration = ClapTextConfig() >>> # Initializing a model (with random weights) from the configuration >>> model = ClapTextModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```clap_text_model text_configiY vocab_size hidden_size num_hidden_layersnum_attention_headsi intermediate_sizegelu hidden_act皙?hidden_dropout_probattention_probs_dropout_probimax_position_embeddingstype_vocab_size?initializer_factorg-q=layer_norm_epsprojection_dimN pad_token_idr bos_token_id eos_token_idreluprojection_hidden_act)__name__ __module__ __qualname____firstlineno____doc__ model_typebase_config_keyrint__annotations__rrrrrstrrfloatrrrrrr!r"r#r%listr'__static_attributes__r(|/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/clap/configuration_clap.pyr r s #J#OJKs!!!s!J'**03 %#+3#&S&OS ##!NE!NC L#*  L#* +,L#S /D(,!'3'r6r c\rSrSr%SrSrSrSr\\ S'Sr \\ S'S r \\ S 'S r \ \ S 'S r\\\-\\\4-\ S'Sr\\\-\\S4-\ S'Sr\\ S'Sr\\ S'Sr\\ S'Sr\\\\S4-\ S'Sr\\\\S4-\ S'Sr\\ S'Sr\\-\ S'S r\ S -\ S!'S"r\\ S#'S$r\\ S%'S&r\\ S''S$r\\ S('S)r \\-\ S*'S)r!\\-\ S+'S$r"\\ S,'S-r#\\ S.'S r$\\ S/'S r%\\ S0'S1r&\ \ S2'S3r'\\ S4'S5r(\\ S6'S7r)g )8ClapAudioConfigBa^ window_size (`int`, *optional*, defaults to 8): Image size of the spectrogram spec_size (`int`, *optional*, defaults to 256): Desired input size of the spectrogram that the model supports. It can be different from the output of the `ClapFeatureExtractor`, in which case the input features will be resized. Corresponds to the `image_size` of the audio models. patch_stride (`list`, *optional*, defaults to `[4, 4]`): Patch stride for the audio spectrogram num_classes (`int`, *optional*, defaults to 527): Number of classes used for the head training enable_fusion (`bool`, *optional*, defaults to `False`): Whether or not to enable patch fusion. This is the main contribution of the authors, and should give the best results. fusion_type (`[type]`, *optional*): Fusion type used for the patch fusion. patch_embed_input_channels (`int`, *optional*, defaults to 1): Number of channels used for the input spectrogram flatten_patch_embeds (`bool`, *optional*, defaults to `True`): Whether or not to flatten the patch embeddings patch_embeds_hidden_size (`int`, *optional*, defaults to 96): Hidden size of the patch embeddings. It is used as the number of output channels. enable_patch_layer_norm (`bool`, *optional*, defaults to `True`): Whether or not to enable layer normalization for the patch embeddings aff_block_r (`int`, *optional*, defaults to 4): downsize_ratio used in the AudioFF block Example: ```python >>> from transformers import ClapAudioConfig, ClapAudioModel >>> # Initializing a ClapAudioConfig with laion/clap-htsat-fused style configuration >>> configuration = ClapAudioConfig() >>> # Initializing a ClapAudioModel (with random weights) from the laion/clap-htsat-fused style configuration >>> model = ClapAudioModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```clap_audio_model audio_config window_size@ num_mel_bins spec_sizerr patch_size)rCrC. patch_stridei num_classesrrr r!)r$r$r$depths)rCr= rF enable_fusionrrN fusion_typerpatch_embed_input_channelsTflatten_patch_embeds`patch_embeds_hidden_sizeenable_patch_layer_normgdrop_path_raterqkv_biasg@ mlp_ratio aff_block_rrr&r'gh㈵>rrrr()*r)r*r+r,r-r.r/r>r0r1r@rBrr2rDr4tuplerErFrr!rHrrKboolrr3rLrMrNrPrQrRrrSrTrUrr'rrr5r(r6r7r9r9Bs( T$J$OKL#IsJ45Jd3i%S/156>> from transformers import ClapConfig, ClapModel >>> # Initializing a ClapConfig with laion-ai/base style configuration >>> configuration = ClapConfig() >>> # Initializing a ClapModel (with random weights) from the laion-ai/base style configuration >>> model = ClapModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config >>> # We can also initialize a ClapConfig from a ClapTextConfig and a ClapAudioConfig >>> from transformers import ClapTextConfig, ClapAudioConfig >>> # Initializing a ClapText and ClapAudioConfig configuration >>> config_text = ClapTextConfig() >>> config_audio = ClapAudioConfig() >>> config = ClapConfig(text_config=config_text, audio_config=config_audio) ```clap)r r<Nr r<g$I$I,@logit_scale_init_valuer r!r&r'rrc V>URc%[5Ul[RS5 O9[ UR[ 5(a[S0URD6UlUR c%[5Ul[RS5 O9[ UR [ 5(a[S0UR D6UlURURlURUR lURURl URUR l URRUl URR[UR R5-Ul [TU]<"S0UD6 g)NzO`text_config` is `None`. initializing the `ClapTextConfig` with default values.zQ`audio_config` is `None`. initializing the `ClapAudioConfig` with default values.r()r r loggerinfo isinstancedictr<r9r!r'rrlenrHsuper __post_init__)selfkwargs __class__s r7rdClapConfig.__post_init__s;    #-/D  KKi j (($ / /-A0@0@AD     $ / 1D  KKk l ))4 0 0 / D$2C2C DD *.*=*='+/+>+>(151K1K.262L2L/++77!%!1!1!C!Cc$J[J[JbJbFc!c ''r6)r<rrr )r)r*r+r,r-r.r r9 sub_configsr rarr1r<r\r3r!r0r'r2rrdr5 __classcell__)rgs@r7rYrYsx 2J"0/RK26K((4/637L$))D07$,E,NC!'3' ##((r6rY)r9rYr N)r-huggingface_hub.dataclassesrconfiguration_utilsrutilsrr get_loggerr)r^r r9rY__all__r(r6r7rps.3,   H %34$(%$(5$(N34H$&H$5H$V348(!8(58(v >r6