
    Ph<                         d dl mZ ddlmZmZ  G d de      Z G d de      Z G d d	e      Z G d
 de      Zg dZ	y)   )PretrainedConfig   )CONFIG_MAPPING
AutoConfigc                   L     e Zd ZdZdZdZdeiZ	 	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZ	S )EdgeTamVisionConfiga  
    This is the configuration class to store the configuration of a [`EdgeTamVisionModel`]. It is used to instantiate a SAM
    vision encoder according to the specified arguments, defining the model architecture. Instantiating a configuration
    defaults will yield a similar configuration to that of SAM 2.1 Hiera-tiny
    [facebook/EdgeTAM](https://huggingface.co/facebook/EdgeTAM) architecture.

    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
    documentation from [`PretrainedConfig`] for more information.

    Args:
        backbone_config (`Union[dict, "PretrainedConfig"]`, *optional*):
            Configuration for the vision backbone. This is used to instantiate the backbone using
            `AutoModel.from_config`.
        backbone_channel_list (`List[int]`, *optional*, defaults to `[384, 192, 96, 48]`):
            The list of channel dimensions for the backbone.
        backbone_feature_sizes (`List[List[int]]`, *optional*, defaults to `[[256, 256], [128, 128], [64, 64]]`):
            The spatial sizes of the feature maps from the backbone.
        fpn_hidden_size (`int`, *optional*, defaults to 256):
            The hidden dimension of the FPN.
        fpn_kernel_size (`int`, *optional*, defaults to 1):
            The kernel size for the convolutions in the neck.
        fpn_stride (`int`, *optional*, defaults to 1):
            The stride for the convolutions in the neck.
        fpn_padding (`int`, *optional*, defaults to 0):
            The padding for the convolutions in the neck.
        fpn_top_down_levels (`List[int]`, *optional*, defaults to `[2, 3]`):
            The levels for the top-down FPN connections.
        num_feature_levels (`int`, *optional*, defaults to 3):
            The number of feature levels from the FPN to use.
        hidden_act (`str`, *optional*, defaults to `"gelu"`):
            The non-linear activation function in the neck.
        layer_norm_eps (`float`, *optional*, defaults to 1e-06):
            The epsilon for the layer normalization.
        initializer_range (`float`, *optional*, defaults to 0.02):
            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.

    vision_configedgetam_vision_modelbackbone_configc                    t        |   di | |g dn|}|ddgddgddggn|}|ddgn|}t        |t              r'|j	                  dd      |d<   t        |d      di |}n2t        |t              r|}n|t        j                  d	dd
g dd      }|| _        || _	        || _
        || _        || _        || _        || _        || _        |	| _        |
| _        || _        || _        y )N)i     `   0         @   r   r   
model_typetimm_wrapperztimm/repvit_m1.dist_in1kT)       r   r   )in_chansfeatures_onlyout_indices)
model_args )super__init__
isinstancedictgetr   r   from_pretrainedr   backbone_channel_listbackbone_feature_sizesfpn_hidden_sizefpn_kernel_size
fpn_stridefpn_paddingfpn_top_down_levelsnum_feature_levels
hidden_actlayer_norm_epsinitializer_range)selfr   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   kwargs	__class__s                 k/var/www/html/saasai/venv/lib/python3.12/site-packages/transformers/models/edgetam/configuration_edgetam.pyr   zEdgeTamVisionConfig.__init__G   s(     	"6"6K6S 2Yn2H2Pc3Z#sb"X.Vl 	 )<(Cq!fI\ot,,;,?,?n,]OL),_\-JK^o^O4-O$(88*()DQ]^O
  / &;"&<#..$&#6 "4$,!2    )NNNr   r   r   r   Nr   geluư>{Gz?)
__name__
__module____qualname____doc__base_config_keyr   r   sub_configsr   __classcell__r/   s   @r0   r   r      sQ    $L &O'J:K "# 13 13r1   r   c                   8     e Zd ZdZdZ	 	 	 	 	 	 	 	 d fd	Z xZS )EdgeTamPromptEncoderConfigaB  
    This is the configuration class to store the configuration of a [`EdgeTamPromptEncoder`]. The [`EdgeTamPromptEncoder`]
    module is used to encode the input 2D points and bounding boxes.

    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 256):
            Dimensionality of the hidden states.
        image_size (`int`, *optional*, defaults to 1024):
            The expected output resolution of the image.
        patch_size (`int`, *optional*, defaults to 16):
            The size (resolution) of each patch.
        mask_input_channels (`int`, *optional*, defaults to 16):
            The number of channels to be fed to the `MaskDecoder` module.
        num_point_embeddings (`int`, *optional*, defaults to 4):
            The number of point embeddings to be used.
        hidden_act (`str`, *optional*, defaults to `"gelu"`):
            The non-linear activation function in the encoder and pooler.
        layer_norm_eps (`float`, *optional*, defaults to 1e-06):
            The epsilon used by the layer normalization layers.
        scale (`float`, *optional*, defaults to 1):
            The scale factor for the prompt encoder.
    prompt_encoder_configc	                     t        
|   di |	 || _        || _        || _        || _        || _        || _        || _        || _	        y Nr   )
r   r   hidden_size
image_size
patch_sizemask_input_channelsnum_point_embeddingsr*   r+   scale)r-   rB   rC   rD   rE   rF   r*   r+   rG   r.   r/   s             r0   r   z#EdgeTamPromptEncoderConfig.__init__   sQ     	"6"&$$#6 $8!$,
r1   )r   i      rH      r2   r3   r   r5   r6   r7   r8   r9   r   r;   r<   s   @r0   r>   r>   {   s3    4 .O  r1   r>   c                   @     e Zd ZdZdZ	 	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )EdgeTamMaskDecoderConfiga  
    This is the configuration class to store the configuration of a [`EdgeTamMaskDecoder`]. It is used to instantiate a EDGETAM
    memory encoder according to the specified arguments, defining the model 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 256):
            Dimensionality of the hidden states.
        hidden_act (`str`, *optional*, defaults to `"gelu"`):
            The non-linear activation function in the EDGETAM mask decoder.
        mlp_dim (`int`, *optional*, defaults to 2048):
            The dimension of the MLP in the two-way transformer.
        num_hidden_layers (`int`, *optional*, defaults to 2):
            The number of hidden layers in the two-way transformer.
        num_attention_heads (`int`, *optional*, defaults to 8):
            The number of attention heads in the two-way transformer.
        attention_downsample_rate (`int`, *optional*, defaults to 2):
            The downsample rate for the attention layers.
        num_multimask_outputs (`int`, *optional*, defaults to 3):
            The number of multimask outputs.
        iou_head_depth (`int`, *optional*, defaults to 3):
            The depth of the IoU head.
        iou_head_hidden_dim (`int`, *optional*, defaults to 256):
            The hidden dimension of the IoU head.
        dynamic_multimask_via_stability (`bool`, *optional*, defaults to `True`):
            Whether to use dynamic multimask via stability.
        dynamic_multimask_stability_delta (`float`, *optional*, defaults to 0.05):
            The stability delta for the dynamic multimask.
        dynamic_multimask_stability_thresh (`float`, *optional*, defaults to 0.98):
            The stability threshold for the dynamic multimask.

    mask_decoder_configc                     t        |   di | || _        || _        || _        || _        |	| _        |
| _        || _        || _	        || _
        || _        || _        || _        || _        y rA   )r   r   rB   num_multimask_outputsr*   iou_head_depthiou_head_hidden_dimdynamic_multimask_via_stability!dynamic_multimask_stability_delta"dynamic_multimask_stability_threshnum_hidden_layersnum_attention_headsmlp_dimattention_downsample_rate)r-   rB   r*   rW   rU   rV   rX   rO   rP   rQ   rR   rS   rT   r.   r/   s                 r0   r   z!EdgeTamMaskDecoderConfig.__init__   s}      	"6"&%:"$,#6 /N,1R.2T/ "3&#6 )B&r1   )r   r2   i   r      r   r   r   r   Tg?g\(\?rJ   r<   s   @r0   rL   rL      sB    !F ,O "#(,*.+/ C  Cr1   rL   c                   <     e Zd ZdZdZeeedZ	 	 	 	 d fd	Z	 xZ
S )EdgeTamConfiga|	  
    [`EdgeTamConfig`] is the configuration class to store the configuration of a [`EdgeTamModel`]. It is used to instantiate a
    EDGETAM model according to the specified arguments, defining the memory attention, memory encoder, and image encoder
    configs. Instantiating a configuration defaults will yield a similar configuration to that of the SAM 2.1 Hiera-tiny
    [facebook/edgetam.1-hiera-tiny](https://huggingface.co/facebook/edgetam.1-hiera-tiny) architecture.

    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
    documentation from [`PretrainedConfig`] for more information.

    Args:
        vision_config (Union[`dict`, `EdgeTamVisionConfig`], *optional*):
            Dictionary of configuration options used to initialize [`EdgeTamVisionConfig`].
        prompt_encoder_config (Union[`dict`, `EdgeTamPromptEncoderConfig`], *optional*):
            Dictionary of configuration options used to initialize [`EdgeTamPromptEncoderConfig`].
        mask_decoder_config (Union[`dict`, `EdgeTamMaskDecoderConfig`], *optional*):
            Dictionary of configuration options used to initialize [`EdgeTamMaskDecoderConfig`].
        initializer_range (`float`, *optional*, defaults to 0.02):
            Standard deviation for parameter initialization.

    Example:

    ```python
    >>> from transformers import (
    ...     EdgeTamVisionConfig,
    ...     EdgeTamPromptEncoderConfig,
    ...     EdgeTamMaskDecoderConfig,
    ...     EdgeTamModel,
    ... )

    >>> # Initializing a EdgeTamConfig with `"facebook/edgetam.1_hiera_tiny"` style configuration
    >>> configuration = EdgeTamconfig()

    >>> # Initializing a EdgeTamModel (with random weights) from the `"facebook/edgetam.1_hiera_tiny"` style configuration
    >>> model = EdgeTamModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config

    >>> # We can also initialize a EdgeTamConfig from a EdgeTamVisionConfig, EdgeTamPromptEncoderConfig, and EdgeTamMaskDecoderConfig

    >>> # Initializing EDGETAM vision encoder, memory attention, and memory encoder configurations
    >>> vision_config = EdgeTamVisionConfig()
    >>> prompt_encoder_config = EdgeTamPromptEncoderConfig()
    >>> mask_decoder_config = EdgeTamMaskDecoderConfig()

    >>> config = EdgeTamConfig(vision_config, prompt_encoder_config, mask_decoder_config)
    ```edgetam)r	   r?   rM   c                    t        |   di | ||ni }||ni }||ni }t        |t              r&|j	                  dd      |d<   t        |d      di |}t        |t              r|j                         }t        |t              r|j                         }|| _	        t        di || _
        t        di || _        || _        y )Nr   r
   r   )r   r   r   r   r    r   r>   to_dictrL   r	   r?   rM   r,   )r-   r	   r?   rM   r,   r.   r/   s         r0   r   zEdgeTamConfig.__init__0  s     	"6")6)B9N9Z 5`b5H5T1Z\mT**7*;*;LJ`*aM,'*=+FGX-XM+-GH$9$A$A$C!)+CD"5"="="?*%?%XBW%X"#;#R>Q#R !2r1   )NNNr4   )r5   r6   r7   r8   r   r   r>   rL   r:   r   r;   r<   s   @r0   r[   r[      s8    .` J#!;7K " 3 3r1   r[   )r[   r   r>   rL   N)
configuration_utilsr   autor   r   r   r>   rL   r[   __all__r   r1   r0   <module>rb      sU   , 4 -^3* ^3B1!1 1hFC/ FCRQ3$ Q3h mr1   