o iH@sdZddlmZddlmZddlmZmZmZddl m Z ddl m Z ddl mZer8dd lmZdd l mZeeZGd d d e ZGd dde ZGddde ZGddde ZgdZdS)zGroupViT model configuration OrderedDict)Mapping) TYPE_CHECKINGAnyOptional)PretrainedConfig) OnnxConfig)logging)ProcessorMixin) TensorTypecsHeZdZdZdZdZ         dfdd ZZS)GroupViTTextConfiga> This is the configuration class to store the configuration of a [`GroupViTTextModel`]. It is used to instantiate an GroupViT 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 GroupViT [nvidia/groupvit-gcc-yfcc](https://huggingface.co/nvidia/groupvit-gcc-yfcc) 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 49408): Vocabulary size of the GroupViT text model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`GroupViTModel`]. hidden_size (`int`, *optional*, defaults to 256): Dimensionality of the encoder layers and the pooler layer. intermediate_size (`int`, *optional*, defaults to 1024): Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 4): Number of attention heads for each attention layer in the Transformer encoder. max_position_embeddings (`int`, *optional*, defaults to 77): 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). hidden_act (`str` or `function`, *optional*, defaults to `"quick_gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` `"quick_gelu"` are supported. layer_norm_eps (`float`, *optional*, defaults to 1e-5): The epsilon used by the layer normalization layers. attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. dropout (`float`, *optional*, defaults to 0.0): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. 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 GroupViTTextConfig, GroupViTTextModel >>> # Initializing a GroupViTTextModel with nvidia/groupvit-gcc-yfcc style configuration >>> configuration = GroupViTTextConfig() >>> model = GroupViTTextModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```groupvit_text_model text_config M quick_geluh㈵>{Gz??c sftjd| ||d|||_||_||_| |_||_||_||_||_ ||_ | |_ | |_ | |_ dS)N) pad_token_id bos_token_id eos_token_id)super__init__ vocab_size hidden_sizeintermediate_sizedropoutnum_hidden_layersnum_attention_headsmax_position_embeddingslayer_norm_eps hidden_actinitializer_rangeinitializer_factorattention_dropout)selfr%r&r'r)r*r+r-r,r(r0r.r/rr r!kwargs __class__r"p/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/transformers/models/groupvit/configuration_groupvit.pyr$[s zGroupViTTextConfig.__init__)rrrrrrrrrrrrrrr__name__ __module__ __qualname____doc__ model_typebase_config_keyr$ __classcell__r"r"r3r5r"s(5rcs^eZdZdZdZdZddgddgdgd d d d d dddddddddgffdd ZZS)GroupViTVisionConfiga@ This is the configuration class to store the configuration of a [`GroupViTVisionModel`]. It is used to instantiate an GroupViT 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 GroupViT [nvidia/groupvit-gcc-yfcc](https://huggingface.co/nvidia/groupvit-gcc-yfcc) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: hidden_size (`int`, *optional*, defaults to 384): Dimensionality of the encoder layers and the pooler layer. intermediate_size (`int`, *optional*, defaults to 1536): Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. depths (`list[int]`, *optional*, defaults to [6, 3, 3]): The number of layers in each encoder block. num_group_tokens (`list[int]`, *optional*, defaults to [64, 8, 0]): The number of group tokens for each stage. num_output_groups (`list[int]`, *optional*, defaults to [64, 8, 8]): The number of output groups for each stage, 0 means no group. num_attention_heads (`int`, *optional*, defaults to 6): Number of attention heads for each attention layer in the Transformer encoder. image_size (`int`, *optional*, defaults to 224): The size (resolution) of each image. patch_size (`int`, *optional*, defaults to 16): The size (resolution) of each patch. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` `"quick_gelu"` are supported. layer_norm_eps (`float`, *optional*, defaults to 1e-5): The epsilon used by the layer normalization layers. dropout (`float`, *optional*, defaults to 0.0): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. 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 GroupViTVisionConfig, GroupViTVisionModel >>> # Initializing a GroupViTVisionModel with nvidia/groupvit-gcc-yfcc style configuration >>> configuration = GroupViTVisionConfig() >>> model = GroupViTVisionModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```groupvit_vision_model vision_configii)rrr)@r)rBrCrCrArgelurrrrg?rc stjdi|||_||_||_|t|kr%td|dt|||_||_ ||_ ||_ ||_ | |_ | |_| |_| |_| |_||_||_||_||_||_dS)Nz&Manually setting num_hidden_layers to z1, but we expect num_hidden_layers = sum(depth) = r")r#r$r&r'depthssumloggerwarningr)num_group_tokensnum_output_groupsr* image_size patch_size num_channelsr-r,r(r0r.r/ assign_epsassign_mlp_ratio)r1r&r'rGr)rKrLr*rMrNrOr-r,r(r0r.r/rPrQr2r3r"r5r$s2  zGroupViTVisionConfig.__init__r6r"r"r3r5r>~s.7r>cs:eZdZdZdZeedZ     d fdd ZZ S) GroupViTConfiga [`GroupViTConfig`] is the configuration class to store the configuration of a [`GroupViTModel`]. It is used to instantiate a GroupViT model according to the specified arguments, defining the text model and vision model configs. Instantiating a configuration with the defaults will yield a similar configuration to that of the GroupViT [nvidia/groupvit-gcc-yfcc](https://huggingface.co/nvidia/groupvit-gcc-yfcc) 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 [`GroupViTTextConfig`]. vision_config (`dict`, *optional*): Dictionary of configuration options used to initialize [`GroupViTVisionConfig`]. projection_dim (`int`, *optional*, defaults to 256): Dimensionality of text and vision projection layers. projection_intermediate_dim (`int`, *optional*, defaults to 4096): Dimensionality of intermediate layer of text and vision projection layers. logit_scale_init_value (`float`, *optional*, defaults to 2.6592): The initial value of the *logit_scale* parameter. Default is used as per the original GroupViT implementation. kwargs (*optional*): Dictionary of keyword arguments. groupvit)rr@Nr/L F@c s|dd}|dd}tjdi||dur]|duri}tdi|} | D]+\} } | |vrW| || krW| dkrW| |vrLd| d| d} nd| d} t| q,|| |dur|durgi}t di|} d | vrd d | d D| d <| D]+\} } | |vr| || kr| dkr| |vrd| d | d} nd | d} t| q|| |duri}td|duri}tdtdi||_ t di||_ ||_ ||_ ||_d|_d|_d|_dS)Ntext_config_dictvision_config_dicttransformers_version`zp` is found in both `text_config_dict` and `text_config` but with different values. The value `text_config_dict["z"]` will be used instead.zn`text_config_dict` is provided which will be used to initialize `GroupViTTextConfig`. The value `text_config["z"]` will be overridden.id2labelcSsi|] \}}t||qSr")str).0keyvaluer"r"r5 >sz+GroupViTConfig.__init__..zv` is found in both `vision_config_dict` and `vision_config` but with different values. The value `vision_config_dict["zt`vision_config_dict` is provided which will be used to initialize `GroupViTVisionConfig`. The value `vision_config["zS`text_config` is `None`. Initializing the `GroupViTTextConfig` with default values.zW`vision_config` is `None`. initializing the `GroupViTVisionConfig` with default values.rrFr")popr#r$rto_dictitemsrIinfoupdater>rr@projection_dimprojection_intermediate_dimlogit_scale_init_valuer.r/output_segmentation)r1rr@rerfrgr2rVrW_text_config_dictr]r^message_vision_config_dictr3r"r5r$sr          zGroupViTConfig.__init__)NNrrTrU) r7r8r9r:r;rr> sub_configsr$r=r"r"r3r5rRs rRc seZdZedeeeeefffddZedeeeeefffddZede fddZ   dd d d ed ede ddeee ff fdd Z edefddZZS)GroupViTOnnxConfigreturncCs0tddddfdddddd fd dddfgS) N input_idsbatchsequence)rr pixel_valuesrOheightwidth)rrrattention_maskrr1r"r"r5inputsjs   zGroupViTOnnxConfig.inputscCs0tdddifdddifdddifdddifgS)Nlogits_per_imagerrplogits_per_text text_embeds image_embedsrrwr"r"r5outputsts    zGroupViTOnnxConfig.outputscCdS)Ng-C6?r"rwr"r"r5atol_for_validationz&GroupViTOnnxConfig.atol_for_validationN processorr batch_size seq_length frameworkr cs6tj|j|||d}tj|j||d}i||S)N)rrr)rr)r#generate_dummy_inputs tokenizerimage_processor)r1rrrrtext_input_dictimage_input_dictr3r"r5rs  z(GroupViTOnnxConfig.generate_dummy_inputscCr~)Nr"rwr"r"r5default_onnx_opsetrz%GroupViTOnnxConfig.default_onnx_opset)rrN)r7r8r9propertyrr[intrxr}floatrrrrrr=r"r"r3r5rmis.    rm)rRrmrr>N)r: collectionsrcollections.abcrtypingrrrconfiguration_utilsr onnxr utilsr processing_utilsr r get_loggerr7rIrr>rRrm__all__r"r"r"r5s         \l .