class_docstr: This is the configuration class to store the configuration of a [`SamPromptEncoder`]. The [`SamPromptEncoder`]
  module is used to encode the input 2D points and bounding boxes. Instantiating a configuration defaults will yield
  a similar configuration to that of the SAM-vit-h
  [facebook/sam-vit-huge](https://huggingface.co/facebook/sam-vit-huge) 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.
      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.
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code: def __init__(
      self,
      hidden_size=256,
      image_size=1024,
      patch_size=16,
      mask_input_channels=16,
      num_point_embeddings=4,
      hidden_act="gelu",
      layer_norm_eps=1e-6,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.hidden_size = hidden_size
      self.image_size = image_size
      self.patch_size = patch_size
      self.image_embedding_size = image_size // patch_size
      self.mask_input_channels = mask_input_channels
      self.num_point_embeddings = num_point_embeddings
      self.hidden_act = hidden_act
      self.layer_norm_eps = layer_norm_eps
  
file_path: transformers/src/transformers/models/sam/configuration_sam.py
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new SamPromptEncoderConfig object from inherited base classes: PretrainedConfig with example: obj = SamPromptEncoderConfig(hidden_size, image_size, patch_size, mask_input_channels, num_point_embeddings, hidden_act, layer_norm_eps)