a hH@sdZddlmZddlmZddlmZmZmZddl m Z ddl m Z ddl mZerpdd lmZdd l mZeeZGd d d e ZGd dde ZGddde ZGddde ZgdZdS)zGroupViT model configuration OrderedDict)Mapping) TYPE_CHECKINGAnyOptional)PretrainedConfig) OnnxConfig)logging)ProcessorMixin) TensorTypecs*eZdZdZdZdZdfdd 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 ```Zgroupvit_text_model text_config M quick_geluh㈵>{Gz??c sftjf| ||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&r.r,r-rrr kwargs __class__o/var/www/html/assistant/venv/lib/python3.9/site-packages/transformers/models/groupvit/configuration_groupvit.pyr"[szGroupViTTextConfig.__init__)rrrrrrrrrrrrrrr__name__ __module__ __qualname____doc__ model_typeZbase_config_keyr" __classcell__r3r3r1r4r"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 ```Zgroupvit_vision_model vision_configii)rrr)@r)r?r@r@r>rZgelurrrrg?rc stjfi|||_||_||_|t|krJtd|dt|||_||_ ||_ ||_ ||_ | |_ | |_| |_| |_| |_||_||_||_||_||_dS)Nz&Manually setting num_hidden_layers to z1, but we expect num_hidden_layers = sum(depth) = )r!r"r$r%depthssumloggerwarningr'num_group_tokensnum_output_groupsr( image_size patch_size num_channelsr+r*r&r.r,r- assign_epsassign_mlp_ratio)r/r$r%rCr'rGrHr(rIrJrKr+r*r&r.r,r-rLrMr0r1r3r4r"s2 zGroupViTVisionConfig.__init__r5r3r3r1r4r<~s,7r<cs0eZdZdZdZeedZd 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. Zgroupvit)rr=Nr/L F@c s|dd}|dd}tjfi||dur|dur>i}tfi|} | D]V\} } | |vrX| || krX| dvrX| |vrd| d| d} n d| d} t| qX|| |durz|duri}t fi|} d | vrd d | d D| d <| D]`\} } | |vr| || kr| dvr| |vrVd| d | d} n d | d} t| q|| |duri}td|duri}tdtfi||_ t fi||_ ||_ ||_ ||_d|_d|_d|_dS)Ntext_config_dictvision_config_dict)Ztransformers_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.Zid2labelcSsi|]\}}t||qSr3)str).0keyvaluer3r3r4 >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.rrF)popr!r"rto_dictitemsrEinfoupdater<rr=projection_dimprojection_intermediate_dimlogit_scale_init_valuer,r-Zoutput_segmentation)r/rr=r^r_r`r0rQrRZ_text_config_dictrVrWmessageZ_vision_config_dictr1r3r4r"sn       "      zGroupViTConfig.__init__)NNrrOrP) r6r7r8r9r:rr<Z sub_configsr"r;r3r3r1r4rNs rNcseZdZeeeeeeffdddZeeeeeeffdddZee dddZ dd eee d eee fd fd d Z eedddZZS)GroupViTOnnxConfig)returncCs0tddddfdddddd fd dddfgS) NZ input_idsbatchsequence)rrZ pixel_valuesrKheightwidth)rrrZattention_maskrr/r3r3r4inputsjs   zGroupViTOnnxConfig.inputscCs0tdddifdddifdddifdddifgS)NZlogits_per_imagerrdZlogits_per_textZ text_embedsZ image_embedsrrir3r3r4outputsts    zGroupViTOnnxConfig.outputscCsdS)Ng-C6?r3rir3r3r4atol_for_validationsz&GroupViTOnnxConfig.atol_for_validationNr r ) processor batch_size seq_length frameworkrccs6tj|j|||d}tj|j||d}i||S)N)rorprq)rorq)r!generate_dummy_inputs tokenizerZimage_processor)r/rnrorprqZtext_input_dictZimage_input_dictr1r3r4rrs z(GroupViTOnnxConfig.generate_dummy_inputscCsdS)Nr3rir3r3r4default_onnx_opsetsz%GroupViTOnnxConfig.default_onnx_opset)rmrmN)r6r7r8propertyrrTintrjrkfloatrlrrrrrur;r3r3r1r4rbis$   rb)rNrbrr<N)r9 collectionsrcollections.abcrtypingrrrZconfiguration_utilsr Zonnxr utilsr Zprocessing_utilsr r Z get_loggerr6rErr<rNrb__all__r3r3r3r4s        \l.