code: def __init__(
      self,
      hidden_size=32,
      hidden_act="relu",
      mlp_dim=64,
      num_hidden_layers=2,
      num_attention_heads=4,
      attention_downsample_rate=2,
      num_multimask_outputs=3,
      iou_head_depth=3,
      iou_head_hidden_dim=32,
      layer_norm_eps=1e-6,
  ):
      self.hidden_size = hidden_size
      self.hidden_act = hidden_act
      self.mlp_dim = mlp_dim
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.attention_downsample_rate = attention_downsample_rate
      self.num_multimask_outputs = num_multimask_outputs
      self.iou_head_depth = iou_head_depth
      self.iou_head_hidden_dim = iou_head_hidden_dim
      self.layer_norm_eps = layer_norm_eps
  
imports: import gc
  import unittest
  import requests
  from transformers import SamConfig, SamMaskDecoderConfig, SamPromptEncoderConfig, SamVisionConfig, pipeline
  from transformers.testing_utils import backend_empty_cache, require_torch, slow, torch_device
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new SamMaskDecoderTester object  with example: obj = SamMaskDecoderTester(hidden_size, hidden_act, mlp_dim, num_hidden_layers, num_attention_heads, attention_downsample_rate, num_multimask_outputs, iou_head_depth, iou_head_hidden_dim, layer_norm_eps)