o eiC@sbdZddlmZddlmZeeZGdddeZGdddeZ Gdd d eZ gd Z d S) zCLAP model configuration)PreTrainedConfig)loggingcsLeZdZdZdZdZ          dfdd ZZS)ClapTextConfiga This is the configuration class to store the configuration of a [`ClapTextModel`]. It is used to instantiate a CLAP 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 CLAP [calp-hsat-fused](https://huggingface.co/laion/clap-hsat-fused) architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: vocab_size (`int`, *optional*, defaults to 30522): Vocabulary size of the CLAP model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`ClapTextModel`]. hidden_size (`int`, *optional*, defaults to 768): Dimensionality of the encoder layers and the pooler layer. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 12): Number of attention heads for each attention layer in the Transformer encoder. intermediate_size (`int`, *optional*, defaults to 3072): Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder. hidden_act (`str` or `Callable`, *optional*, defaults to `"relu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"relu"`, `"relu"`, `"silu"` and `"relu_new"` are supported. hidden_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout ratio for the attention probabilities. max_position_embeddings (`int`, *optional*, defaults to 512): The maximum sequence length that this model might ever be used with. Typically set this to something large just in case (e.g., 512 or 1024 or 2048). type_vocab_size (`int`, *optional*, defaults to 2): The vocabulary size of the `token_type_ids` passed when calling [`ClapTextModel`]. layer_norm_eps (`float`, *optional*, defaults to 1e-12): The epsilon used by the layer normalization layers. projection_hidden_act (`str`, *optional*, defaults to `"relu"`): The non-linear activation function (function or string) in the projection layer. If string, `"gelu"`, `"relu"`, `"silu"` and `"gelu_new"` are supported. projection_dim (`int`, *optional*, defaults to 512) Dimension of the projection head of the `ClapTextModelWithProjection`. 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_configY gelu皙??-q=reluc s|tjdi|||_||_||_||_||_||_||_||_ ||_ ||_ ||_ | |_ | |_| |_| |_||_| |_dSN)super__init__ pad_token_id bos_token_id eos_token_id vocab_size hidden_sizenum_hidden_layersnum_attention_heads hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_factorlayer_norm_epsprojection_hidden_actprojection_dim)selfrrrrr!r r"r#r$r%r&r'r)rrrr(kwargs __class__ri/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/transformers/models/clap/configuration_clap.pyrTs$ zClapTextConfig.__init__)rrr r r r r r r rrrrrrrr__name__ __module__ __qualname____doc__ model_typebase_config_keyr __classcell__rrr,r.rs,9rcsleZdZdZdZdZdddddddgd d d gd gd ddddddddddddddddffdd ZZS)ClapAudioConfiga This is the configuration class to store the configuration of a [`ClapAudioModel`]. It is used to instantiate a CLAP audio encoder according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the audio encoder of the CLAP [laion/clap-htsat-fused](https://huggingface.co/laion/clap-htsat-fused) architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: window_size (`int`, *optional*, defaults to 8): Image size of the spectrogram num_mel_bins (`int`, *optional*, defaults to 64): Number of mel features used per frames. Should correspond to the value used in the `ClapProcessor` class. 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. hidden_act (`str`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"silu"` and `"gelu_new"` are supported. patch_size (`int`, *optional*, defaults to 4): Patch size for the audio spectrogram 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 hidden_size (`int`, *optional*, defaults to 768): Hidden size of the output of the audio encoder. Correspond to the dimension of the penultimate layer's output,which is sent to the projection MLP layer. projection_dim (`int`, *optional*, defaults to 512): Hidden size of the projection layer. depths (`list`, *optional*, defaults to `[2, 2, 6, 2]`): Depths used for the Swin Layers of the audio model num_attention_heads (`list`, *optional*, defaults to `[4, 8, 16, 32]`): Number of attention heads used for the Swin Layers of the audio model 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. hidden_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout probability for all fully connected layers in the encoder. 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 drop_path_rate (`float`, *optional*, defaults to 0.0): Drop path rate for the patch fusion attention_probs_dropout_prob (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. qkv_bias (`bool`, *optional*, defaults to `True`): Whether or not to add a bias to the query, key, value projections. mlp_ratio (`float`, *optional*, defaults to 4.0): Ratio of the mlp hidden dim to embedding dim. aff_block_r (`int`, *optional*, defaults to 4): downsize_ratio used in the AudioFF block num_hidden_layers (`int`, *optional*, defaults to 4): Number of hidden layers in the Transformer encoder. projection_hidden_act (`str`, *optional*, defaults to `"relu"`): The non-linear activation function (function or string) in the projection layer. If string, `"gelu"`, `"relu"`, `"silu"` and `"gelu_new"` are supported. layer_norm_eps (`[type]`, *optional*, defaults to 1e-05): The epsilon used by the layer normalization layers. initializer_factor (`float`, *optional*, defaults to 1.0): A factor for initializing all weight matrices (should be kept to 1, used internally for initialization testing). 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@r irr)rrr)r=r: Fr NrT`gg@rgh㈵>rc stjdi|||_||_||_||_||_||_||_| |_ ||_ | |_ ||_| |_ ||_ ||_| |_| |_||_||_||_||_||_||_||_||_||_||_||_||_dSr)rr window_size num_mel_bins spec_size patch_size patch_stride num_classesrdepthsrr enable_fusion fusion_typer r"r)flatten_patch_embedspatch_embeds_hidden_sizeenable_patch_layer_normdrop_path_rater#qkv_bias mlp_ratiopatch_embed_input_channels aff_block_rr'r&r()r*rBrCrDr rErFrGrr)rHrrIr"rJrQrKrLrMrNr#rOrPrRrr(r'r&r+r,rr.rs: zClapAudioConfig.__init__r/rrr,r.r7~s@Wr7cs<eZdZdZdZeedZ      d fd d ZZ S) ClapConfiga+ [`ClapConfig`] is the configuration class to store the configuration of a [`ClapModel`]. It is used to instantiate a CLAP model according to the specified arguments, defining the text model and audio model configs. Instantiating a configuration with the defaults will yield a similar configuration to that of the CLAP [laion/clap-htsat-fused](https://huggingface.co/laion/clap-htsat-fused) architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: text_config (`dict`, *optional*): Dictionary of configuration options used to initialize [`ClapTextConfig`]. audio_config (`dict`, *optional*): Dictionary of configuration options used to initialize [`ClapAudioConfig`]. logit_scale_init_value (`float`, *optional*, defaults to 14.29): The initial value of the *logit_scale* parameter. Default is used as per the original CLAP implementation. projection_dim (`int`, *optional*, defaults to 512): Dimensionality of text and audio projection layers. projection_hidden_act (`str`, *optional*, defaults to `"relu"`): Activation function for the projection layers. initializer_factor (`float`, *optional*, defaults to 1.0): Factor to scale the initialization of the model weights. kwargs (*optional*): Dictionary of keyword arguments. Example: ```python >>> 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)rr9N$I$I,@rrrc s|dur t}tdn t|trtdi|}|dur&t}tdn t|tr2tdi|}||_||_||j_||j_||j_ ||j_ ||_||_ |jj |_ ||_ ||_ |jj t|jj|_ tjdi|dS)NzO`text_config` is `None`. initializing the `ClapTextConfig` with default values.zQ`audio_config` is `None`. initializing the `ClapAudioConfig` with default values.r)rloggerinfo isinstancedictr7rr9r)r(rlogit_scale_init_valuer&rlenrHrr)r*rr9rZr)r(r&r+r,rr.rLs.      zClapConfig.__init__)NNrUrrr) r0r1r2r3r4rr7 sub_configsrr6rrr,r.rSs1 rS)r7rSrN) r3configuration_utilsrutilsr get_loggerr0rVrr7rS__all__rrrr.s   g ^